{"meta":{"page":1,"per_page":50,"max_per_page":100,"total":525,"total_is_capped":false,"direct_labels_cover":0,"predictions_cover":525,"direct_label_status":"direct model label, unvalidated","prediction_status":"machine_predicted_unvalidated (Codex and Gemma teacher distillation)","score_status":"score_only:v0-immature-baseline (scores rank; they never assert a category)","snapshot":{"source":"OpenAlex, pinned release, all 482 partitions","release":"2026-06-24","frame_built":"2026-07-12","author_layer_release":"2026-06-26"},"query_hash":"2581e8a018d2","filters":{"topic":"Wood and Agarwood Research"}},"results":[{"id":"W2167666191","doi":"10.1007/s00138-012-0417-5","title":"A database for automatic classification of forest species","year":2012,"lang":"en","type":"article","venue":"Machine Vision and Applications","topic":"Wood and Agarwood Research","field":"Chemistry","cited_by":97,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"École de Technologie Supérieure","funders":"Conselho Nacional de Desenvolvimento Científico e Tecnológico; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior","keywords":"Computer science; Benchmarking; Artificial intelligence; Database; Support vector machine; Confusion; Set (abstract data type); Feature (linguistics); Field (mathematics); Pattern recognition (psychology); Feature vector; Machine learning; Mathematics","authors":[{"name":"Jefferson Gustavo Martins","is_ca":false},{"name":"Luiz S. Oliveira","is_ca":false},{"name":"Silvana Nisgoski","is_ca":false},{"name":"Robert Sabourin","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.03735502072411806,"gpt":0.3433906846771851,"spread":0.3060356639530671,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007383159,0.001397017,0.001635296,0.007796462,0.0008375359,0.001332783,0.002412128,0.00123399,0.01481604],"category_scores_gemma":[0.002226986,0.0004896601,0.0008288745,0.006652614,0.00024392,0.001770425,0.001002164,0.0007409129,0.01793988],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000594962,"about_ca_system_score_gemma":0.001645121,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007377085,"about_ca_topic_score_gemma":0.01136032,"domain_scores_codex":[0.9993799,0.00004368282,0.0001178406,0.0001787025,0.0002218898,0.00005791157],"domain_scores_gemma":[0.998015,0.000234151,0.0002023187,0.0005428201,0.0007383635,0.0002672314],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002020835,0.001028664,0.02115104,0.003001701,0.0003461422,0.0006030547,0.000272969,0.003457488,0.06471882,0.00471317,0.414447,0.4842393],"study_design_scores_gemma":[0.0005613915,0.0004788346,0.07602315,0.0003996683,0.0005305395,0.001910678,0.0004910901,0.02144394,0.055425,0.006515191,0.8360097,0.0002106775],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.04455788,0.002317401,0.03277132,0.0001523866,0.0002116256,0.0006027353,0.8901936,0.01679843,0.01239452],"genre_scores_gemma":[0.03117902,0.0008704597,0.04573279,0.0001102411,0.00004111496,0.0005453113,0.9165388,0.0004593335,0.004522827],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01481604,"threshold_uncertainty_score":0.0495646,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W6947763008","doi":"10.3847/2041-8213/adf49a","title":"Discovery and Preliminary Characterization of a Third Interstellar Object: 3I/ATLAS","year":2025,"lang":"en","type":"article","venue":"The Astrophysical Journal Letters","topic":"Wood and Agarwood Research","field":"Chemistry","cited_by":63,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"Ministerio de Ciencia e Innovación; Hertz Foundation; Simons Foundation; Science Fund of the Republic of Serbia; National Aeronautics and Space Administration","keywords":"Observable; Solar System; Telescope; Orbital mechanics; Unobservable; Mars Exploration Program; Eccentricity (behavior); Trans-Neptunian object; Planet","authors":[],"retraction":null,"screen_n_in":null,"score":{"opus":0.005754385280595544,"gpt":0.2252056789686748,"spread":0.2194512936880793,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002139991,0.0003056343,0.0003342655,0.0009909671,0.0009891768,0.001256136,0.0003634733,0.0003483631,0.002037419],"category_scores_gemma":[0.0001582739,0.0001631156,0.0003634469,0.000851971,0.0002977083,0.00034163,0.0006478574,0.000479117,0.0008198966],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000751984,"about_ca_system_score_gemma":0.0004017471,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003365847,"about_ca_topic_score_gemma":0.005552547,"domain_scores_codex":[0.99989,0.000003663298,0.000003584347,0.0000342587,0.00003028558,0.00003820431],"domain_scores_gemma":[0.9995969,0.00001813473,0.00006023837,0.00004818426,0.00005039064,0.0002261166],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.001516119,0.0004964264,0.397904,0.0002411554,0.0002122407,0.003831764,0.001036284,0.001208434,0.5267588,0.004309688,0.007519553,0.05496556],"study_design_scores_gemma":[0.00005232728,0.0005456688,0.871618,0.00003548426,0.0000924194,0.002264193,0.000447896,0.002650839,0.07311197,0.000713936,0.04841303,0.00005405695],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9823062,0.0004209984,0.002087072,0.00009104794,0.00005378995,0.00005096088,0.002421535,0.0002312772,0.0123372],"genre_scores_gemma":[0.9827108,0.0001284367,0.004869347,0.0001487911,0.00004950775,0.00002596311,0.009334005,0.00004278749,0.002690323],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003365847,"threshold_uncertainty_score":0.006815791,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2904716144","doi":"10.1007/s00226-018-1073-3","title":"Classification of thermally treated wood using machine learning techniques","year":2018,"lang":"en","type":"article","venue":"Wood Science and Technology","topic":"Wood and Agarwood Research","field":"Chemistry","cited_by":59,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Artificial intelligence; Support vector machine; Naive Bayes classifier; Artificial neural network; Machine learning; Pattern recognition (psychology); Computer science; Classifier (UML); Mathematics","authors":[{"name":"Vahid Nasir","is_ca":true},{"name":"Sepideh Nourian","is_ca":true},{"name":"Stavros Avramidis","is_ca":true},{"name":"Julie Cool","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.02913400130177321,"gpt":0.3052768226828416,"spread":0.2761428213810684,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000404224,0.0005529191,0.0005189023,0.001598407,0.0002946421,0.0007438482,0.0004126829,0.0006456723,0.001260762],"category_scores_gemma":[0.0007431163,0.0001798919,0.0007091255,0.0008773374,0.0002933731,0.0005996404,0.0001899669,0.0005643769,0.0006088089],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003083436,"about_ca_system_score_gemma":0.0002494655,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001468889,"about_ca_topic_score_gemma":0.001885318,"domain_scores_codex":[0.9997869,0.00002760377,0.00002153539,0.00005285213,0.00007168776,0.00003939878],"domain_scores_gemma":[0.9995142,0.0001724122,0.00006649816,0.00006373494,0.0001618377,0.00002138107],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.001205969,0.000721613,0.01893939,0.000386017,0.0001227904,0.0002851071,0.0001800873,0.09634475,0.4182371,0.001165441,0.001955268,0.4604565],"study_design_scores_gemma":[0.00001853397,0.0004635486,0.03009502,0.00003615942,0.00009256898,0.0001988148,0.0002098247,0.8006299,0.1635157,0.001691886,0.002995626,0.00005237635],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8053965,0.001039148,0.1882035,0.0001400216,0.0002155578,0.0001143992,0.0008293924,0.0009685618,0.003093017],"genre_scores_gemma":[0.9422254,0.000387713,0.05280137,0.0000299032,0.00004001284,0.0000579014,0.00110643,0.00005455813,0.003296753],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001598407,"threshold_uncertainty_score":0.004217625,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2047722496","doi":"10.1371/journal.pone.0107669","title":"DNA Barcode Authentication of Wood Samples of Threatened and Commercial Timber Trees within the Tropical Dry Evergreen Forest of India","year":2014,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Wood and Agarwood Research","field":"Chemistry","cited_by":53,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Guelph","funders":"Core Research for Evolutional Science and Technology; Department of Biotechnology, Ministry of Science and Technology, India; SRM Institute of Science and Technology","keywords":"Threatened species; DNA barcoding; Barcode; Biodiversity; Evergreen; Agroforestry; Evergreen forest; Biology; Near-threatened species; Ecology; Geography; Computer science; Habitat","authors":[{"name":"Stalin Nithaniyal","is_ca":false},{"name":"Steven G. Newmaster","is_ca":true},{"name":"Subramanyam Ragupathy","is_ca":true},{"name":"Devanathan Krishnamoorthy","is_ca":false},{"name":"Sophie Lorraine Vassou","is_ca":false},{"name":"Madasamy Parani","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.04143323066248088,"gpt":0.2427916902312955,"spread":0.2013584595688146,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002689025,0.0001624305,0.0001493436,0.001749832,0.0004903507,0.0004220606,0.0004542776,0.0003979799,0.0006011981],"category_scores_gemma":[0.001074203,0.00009913656,0.0001506329,0.001590409,0.000412627,0.0002612217,0.000358737,0.0003107029,0.0004156592],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002611186,"about_ca_system_score_gemma":0.0003741828,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004566064,"about_ca_topic_score_gemma":0.01278651,"domain_scores_codex":[0.999493,0.00005073716,0.0000506047,0.0001371761,0.0001880751,0.00008035961],"domain_scores_gemma":[0.9990218,0.0001623742,0.0002977923,0.00008342752,0.0003726528,0.00006198749],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0003379011,0.0001659685,0.386816,0.0004581581,0.00004111234,0.0008899007,0.004520508,0.0007312574,0.534556,0.0005259485,0.0007463941,0.07021084],"study_design_scores_gemma":[0.000008659404,0.0004186675,0.851207,0.0001216055,0.00009499765,0.003260118,0.004449038,0.002883043,0.1257429,0.000232554,0.01153911,0.00004227376],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.989993,0.000333188,0.005795465,0.00004704661,0.00002037298,0.0001206258,0.002149858,0.00006133765,0.00147899],"genre_scores_gemma":[0.9750318,0.0003507786,0.01874027,0.0001358591,0.000009063318,0.0001097592,0.004510473,0.00002104949,0.00109098],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004566064,"threshold_uncertainty_score":0.009078979,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2619429263","doi":"10.1163/22941932-20170171","title":"Identification of selected CITES-protected Araucariaceae using DART TOFMS","year":2017,"lang":"en","type":"article","venue":"IAWA Journal - KU Leuven/IAWA Journal","topic":"Wood and Agarwood Research","field":"Chemistry","cited_by":39,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of British Columbia","funders":"Agencia Nacional de Promoción Científica y Tecnológica; FPInnovations; Consejo Nacional de Investigaciones Científicas y Técnicas","keywords":"Araucaria; Biology; Provenance; Botany; Dart; Taxon; Identification (biology); Paleontology","authors":[{"name":"Philip D. Evans","is_ca":true},{"name":"Ignacio A. Mundo","is_ca":false},{"name":"Michael C. Wiemann","is_ca":false},{"name":"Gabriela Chavarría","is_ca":false},{"name":"Pamela J. McClure","is_ca":false},{"name":"Doina Voin","is_ca":false},{"name":"Edgard O. Espinoza","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.04494916398408094,"gpt":0.3305079184429889,"spread":0.285558754458908,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000179995,0.0003111843,0.0002470691,0.001908409,0.0003750258,0.000347789,0.0002527006,0.0002634229,0.001299142],"category_scores_gemma":[0.0004288825,0.00008696462,0.0002195415,0.0008018994,0.0002277085,0.0002356988,0.0002105668,0.0002299441,0.0004678555],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002402598,"about_ca_system_score_gemma":0.00009523139,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002059244,"about_ca_topic_score_gemma":0.005005034,"domain_scores_codex":[0.999881,0.00001249499,0.000009826209,0.00004602424,0.0000323334,0.00001838769],"domain_scores_gemma":[0.9997637,0.0000424074,0.00009349817,0.00001749729,0.00005523983,0.00002773872],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002464882,0.00009106106,0.1571433,0.00009937193,0.00003839498,0.000388858,0.0007593609,0.0001056857,0.7948308,0.00009588384,0.0001156187,0.0460852],"study_design_scores_gemma":[0.00000640581,0.0001858083,0.9773777,0.00001083675,0.00001992822,0.000706983,0.0004902523,0.0004669469,0.01789892,0.00006087624,0.00276366,0.00001167274],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9970619,0.0004823906,0.0004762005,0.00002303614,0.000005353308,0.00001669505,0.0004409702,0.00003103315,0.001462407],"genre_scores_gemma":[0.9932441,0.0004028854,0.003876893,0.00003720724,0.00001076236,0.00003135047,0.001110784,0.00001266451,0.001273375],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002059244,"threshold_uncertainty_score":0.004346073,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1971430271","doi":"10.1007/s10086-008-1013-1","title":"Identification of selected internal wood characteristics in computed tomography images of black spruce: a comparison study","year":2009,"lang":"en","type":"article","venue":"Journal of Wood Science","topic":"Wood and Agarwood Research","field":"Chemistry","cited_by":35,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"FPInnovations; University of New Brunswick","funders":"Natural Sciences and Engineering Research Council of Canada; FPInnovations; New Brunswick Innovation Foundation; Ministry of Natural Resources","keywords":"Black spruce; Classifier (UML); Artificial intelligence; Pattern recognition (psychology); Artificial neural network; Mathematics; Computed tomography; Computer science; Geography; Forestry; Taiga","authors":[{"name":"Qiang Wei","is_ca":true},{"name":"Ying Hei Chui","is_ca":true},{"name":"Brigitte Leblon","is_ca":true},{"name":"Shu Yin Zhang","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.0168489330766186,"gpt":0.3177706430237948,"spread":0.3009217099471762,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004535606,0.0003178953,0.0002344816,0.001482744,0.0002642872,0.0005547252,0.0002254039,0.0003976888,0.001187305],"category_scores_gemma":[0.0007722489,0.0001935921,0.0002628248,0.0005373202,0.0002825896,0.0004437532,0.0002063497,0.000182444,0.00032613],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001652986,"about_ca_system_score_gemma":0.0001789875,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00323085,"about_ca_topic_score_gemma":0.003648643,"domain_scores_codex":[0.9998958,0.00001651352,0.000008376454,0.0000242292,0.0000248696,0.00003023277],"domain_scores_gemma":[0.9993941,0.0001693411,0.00008637377,0.00005495699,0.000222344,0.00007290777],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.002738809,0.000229962,0.1857248,0.0001985957,0.00009773914,0.00126841,0.0004943559,0.0008045046,0.7745561,0.000104803,0.0001240263,0.03365785],"study_design_scores_gemma":[0.00001705884,0.0006304861,0.901791,0.00001956627,0.0001854211,0.004787247,0.0007870606,0.003101703,0.08806487,0.00006066335,0.0005344088,0.00002063569],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9977528,0.0002609221,0.001216847,0.000005867731,0.000001744515,0.00001049081,0.00008801879,0.000009335937,0.0006538762],"genre_scores_gemma":[0.9980987,0.0002237743,0.001148758,0.000008625725,0.000004350025,0.000004398616,0.000159456,0.00001226977,0.0003397437],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00323085,"threshold_uncertainty_score":0.006424069,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2113876505","doi":"10.1007/s00138-015-0659-0","title":"Forest species recognition based on dynamic classifier selection and dissimilarity feature vector representation","year":2015,"lang":"en","type":"article","venue":"Machine Vision and Applications","topic":"Wood and Agarwood Research","field":"Chemistry","cited_by":33,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Pattern recognition (psychology); Artificial intelligence; Scale-invariant feature transform; Local binary patterns; Classifier (UML); Feature vector; Computer science; Feature selection; Support vector machine; Probabilistic logic; Random forest; Mathematics; Feature extraction; Histogram","authors":[{"name":"Jefferson Gustavo Martins","is_ca":false},{"name":"Luiz S. Oliveira","is_ca":false},{"name":"Alceu S. Britto","is_ca":false},{"name":"Robert Sabourin","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.03403744080307197,"gpt":0.3272146374337217,"spread":0.2931771966306497,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005201128,0.0004426854,0.00106817,0.002621296,0.0005422994,0.000733998,0.0008613322,0.0004152065,0.001540252],"category_scores_gemma":[0.0009569374,0.0002241952,0.0006872781,0.001764051,0.0002323186,0.001017151,0.0006006632,0.0003907974,0.000623755],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003874449,"about_ca_system_score_gemma":0.0005079923,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002554781,"about_ca_topic_score_gemma":0.003952579,"domain_scores_codex":[0.9995494,0.00003352224,0.00002412974,0.0001659754,0.0001467769,0.00008004167],"domain_scores_gemma":[0.999508,0.0001044528,0.00005090994,0.00004968018,0.0002427675,0.00004430478],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000365484,0.0002713594,0.01003584,0.00007195482,0.0000819832,0.0001170164,0.00009180545,0.01504453,0.1103967,0.001748299,0.002981605,0.8587934],"study_design_scores_gemma":[0.00002627592,0.0001506483,0.01636441,0.000009891856,0.00006707943,0.000448692,0.0001002367,0.9523923,0.02420603,0.003142851,0.00305296,0.00003854407],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2274175,0.0004836284,0.7667497,0.0001241883,0.0001411996,0.0001549344,0.0004412291,0.00156171,0.002925847],"genre_scores_gemma":[0.7254919,0.0002133138,0.270511,0.00006631367,0.00009156516,0.0001499691,0.001231778,0.000116169,0.00212787],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002621296,"threshold_uncertainty_score":0.005152643,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3198644427","doi":"10.1038/s41598-021-96850-2","title":"Rapid identification of wood species using XRF and neural network machine learning","year":2021,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Wood and Agarwood Research","field":"Chemistry","cited_by":32,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Government of Canada; Parks Canada","funders":"Andrew W. Mellon Foundation","keywords":"Identification (biology); Convolutional neural network; Species identification; Artificial neural network; Computer science; Machine learning; Artificial intelligence; Biochemical engineering; Engineering; Ecology; Biology","authors":[{"name":"Aaron Shugar","is_ca":false},{"name":"B Lee Drake","is_ca":false},{"name":"Greg Kelley","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.03362267976593017,"gpt":0.2733155971810923,"spread":0.2396929174151621,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007768091,0.0008039599,0.000449321,0.002324776,0.0005112331,0.0007142485,0.0006555286,0.000897209,0.003197858],"category_scores_gemma":[0.0008552012,0.0003653902,0.0003483059,0.0008880867,0.0003889503,0.001412228,0.0006382582,0.0009001932,0.001330148],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00038611,"about_ca_system_score_gemma":0.0002565856,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001303383,"about_ca_topic_score_gemma":0.003451867,"domain_scores_codex":[0.9995678,0.00004552395,0.0000212396,0.0001176367,0.0002052519,0.00004252017],"domain_scores_gemma":[0.9995484,0.0001341193,0.00008957909,0.00006524717,0.0001424599,0.00002006438],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001455868,0.00008006219,0.003848885,0.0002707304,0.00004371289,0.0003099495,0.00008802424,0.00407152,0.7578648,0.001899838,0.001542787,0.2298342],"study_design_scores_gemma":[0.00003630706,0.0004925139,0.0232418,0.0001249701,0.00005317766,0.002486973,0.000254417,0.2765487,0.656279,0.006345592,0.03399102,0.0001455101],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1542006,0.003993807,0.8312672,0.0004158379,0.0002078799,0.0001616289,0.0009577086,0.002463182,0.006332129],"genre_scores_gemma":[0.2473059,0.001776082,0.7430276,0.0001606901,0.00005946561,0.0001527294,0.000876744,0.0001269579,0.006513899],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003197858,"threshold_uncertainty_score":0.01069784,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W6947769019","doi":"10.3929/ethz-b-000351636","title":"Cardiac MRI Endpoints in Myocardial Infarction Experimental and Clinical Trials: JACC Scientific Expert Panel","year":2019,"lang":"en","type":"article","venue":"Repository for Publications and Research Data (ETH Zurich)","topic":"Wood and Agarwood Research","field":"Chemistry","cited_by":24,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"","funders":"National Heart, Lung, and Blood Institute; Abbott Vascular; Boston Scientific Corporation; Circle Cardiovascular Imaging; Centro Nacional de Investigaciones Cardiovasculares; Ministerio de Ciencia e Innovación; Siemens Healthineers; University of Glasgow; National Institutes of Health; Edwards Lifesciences; GlaxoSmithKline; American College of Cardiology Foundation; AstraZeneca","keywords":"Myocardial infarction; Cardiac magnetic resonance; Clinical trial; Selection (genetic algorithm); Clinical endpoint; Endpoint Determination; Magnetic resonance imaging","authors":[],"retraction":null,"screen_n_in":null,"score":{"opus":0.3578662188688883,"gpt":0.5048092206877833,"spread":0.146943001818895,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.271404,0.002326172,0.007634991,0.005148113,0.00223655,0.009768038,0.01064567,0.01833444,0.01070975],"category_scores_gemma":[0.2432636,0.001673563,0.007407546,0.007854911,0.002051926,0.003294013,0.00592782,0.01154474,0.01106682],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004264633,"about_ca_system_score_gemma":0.02032997,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002794835,"about_ca_topic_score_gemma":0.003137203,"domain_scores_codex":[0.8623996,0.070025,0.03408978,0.004387466,0.02593092,0.003167277],"domain_scores_gemma":[0.6072704,0.1413289,0.05358651,0.01938664,0.1616102,0.01681728],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.002582209,0.0002459716,0.001439259,0.02211738,0.001484233,0.0001210535,0.0003381452,0.0008601581,0.001556792,0.003998409,0.6864938,0.2787625],"study_design_scores_gemma":[0.003751875,0.0004958498,0.0100146,0.06242454,0.002681058,0.0002209497,0.0002055178,0.001771182,0.001640936,0.008223711,0.9083528,0.0002169281],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"other","genre_scores_codex":[0.006836083,0.2826906,0.05092625,0.3783842,0.05766545,0.07626396,0.04231818,0.001983248,0.102932],"genre_scores_gemma":[0.04392455,0.1897966,0.2595446,0.2011622,0.0665276,0.1287821,0.06005661,0.002954981,0.04725084],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.271404,"threshold_uncertainty_score":0.8984885,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2998476348","doi":"10.15376/biores.15.1.317-330","title":"Species- and moisture-based sorting of green timber mix with near infrared spectroscopy","year":2019,"lang":"en","type":"article","venue":"BioResources","topic":"Wood and Agarwood Research","field":"Chemistry","cited_by":22,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of British Columbia","funders":"China Scholarship Council","keywords":"Partial least squares regression; Chemometrics; Support vector machine; Mathematics; Calibration; Sorting; Least squares support vector machine; Mean squared error; Moisture; Cross-validation; Linear discriminant analysis; Coefficient of determination; Water content; Pattern recognition (psychology); Analytical Chemistry (journal); Statistics; Artificial intelligence; Algorithm; Chemistry; Computer science; Engineering; Machine learning; Chromatography","authors":[{"name":"Zhu Zhou","is_ca":true},{"name":"Sohrab Rahimi","is_ca":true},{"name":"Stavros Avramidis","is_ca":true},{"name":"Yiming Fang","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.00904401943039655,"gpt":0.2220171207500965,"spread":0.2129731013197,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009070482,0.0006184386,0.0004666474,0.001219303,0.0002321638,0.0004038685,0.0003100865,0.0003325041,0.0008162285],"category_scores_gemma":[0.0007742068,0.0002549386,0.0003662474,0.0006791005,0.0001975313,0.000423657,0.000299694,0.0003120218,0.0004641571],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001977499,"about_ca_system_score_gemma":0.0002231705,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009778967,"about_ca_topic_score_gemma":0.003706525,"domain_scores_codex":[0.9996601,0.00004770992,0.00001964453,0.0001106394,0.000142747,0.00001905033],"domain_scores_gemma":[0.9997458,0.00006681548,0.00004826953,0.00002231038,0.00009495128,0.00002185498],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000230771,0.0001188539,0.01578848,0.0001013599,0.00003971075,0.00003294141,0.00006488691,0.002847643,0.9213606,0.0001044865,0.0001278755,0.0591823],"study_design_scores_gemma":[0.00003163242,0.0004796665,0.1292048,0.00001738582,0.0001289522,0.0002069163,0.0001818394,0.1453444,0.7218204,0.0005279543,0.001973464,0.00008251917],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9044243,0.0005918918,0.09248026,0.00003762184,0.00003324209,0.000148345,0.000486299,0.0004339981,0.001364084],"genre_scores_gemma":[0.852313,0.0004185278,0.1442074,0.00005440743,0.00001932062,0.0001108505,0.0005884948,0.00006672702,0.002221296],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001219303,"threshold_uncertainty_score":0.004796982,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4385858713","doi":"10.22382/wfs-2023-10","title":"Fiber Quality Prediction Using Nir Spectral Data: Tree-Based Ensemble Learning VS Deep Neural Networks","year":2023,"lang":"en","type":"article","venue":"Wood and Fiber Science","topic":"Wood and Agarwood Research","field":"Chemistry","cited_by":21,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of British Columbia","funders":"U.S. Forest Service; National Science Foundation; University of Georgia; U.S. Department of Agriculture; U.S. Department of Energy; National Institute of Food and Agriculture","keywords":"Random forest; Artificial neural network; Gradient boosting; Artificial intelligence; Boosting (machine learning); Dimensionality reduction; Principal component analysis; Multilayer perceptron; Computer science; Extreme learning machine; Pattern recognition (psychology); Decision tree; Convolutional neural network; Machine learning; Support vector machine","authors":[{"name":"Vahid Nasir","is_ca":true},{"name":"Syed Danish Ali","is_ca":false},{"name":"Ahmad Mohammadpanah","is_ca":false},{"name":"Sameen Raut","is_ca":false},{"name":"Mohamad Nabavi","is_ca":false},{"name":"Joseph Dahlen","is_ca":false},{"name":"Laurence R. Schimleck","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.0655593283818961,"gpt":0.3278357918899483,"spread":0.2622764635080522,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001658259,0.0009846344,0.001051663,0.0007951163,0.0002703149,0.000606427,0.0008127816,0.0007323512,0.0004635252],"category_scores_gemma":[0.001965209,0.0002677201,0.0008066469,0.0006147469,0.0001843226,0.001201276,0.0005207021,0.001201503,0.0002360545],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004939695,"about_ca_system_score_gemma":0.0005609537,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008498412,"about_ca_topic_score_gemma":0.009723033,"domain_scores_codex":[0.9997078,0.00007714202,0.0000191903,0.00008782589,0.00006058793,0.00004754241],"domain_scores_gemma":[0.9992839,0.0002942485,0.00006489539,0.0000760418,0.0002413126,0.0000396718],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003765436,0.0003498397,0.01326502,0.00007696524,0.000287005,0.00007296296,0.0000590761,0.6767216,0.003527024,0.001181085,0.002167256,0.3019157],"study_design_scores_gemma":[0.000002812292,0.00002522328,0.0005813218,0.000005104058,0.00001477035,0.000004649545,0.000005273189,0.9985027,0.0003902251,0.0003703771,0.00009417045,0.000003334054],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4825113,0.007134603,0.5026451,0.001063407,0.0003444895,0.00009704706,0.0006241053,0.001699814,0.003880226],"genre_scores_gemma":[0.9443262,0.0009517969,0.05220316,0.0001770993,0.0001055247,0.00004663042,0.0006578339,0.00003444916,0.001497401],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008498412,"threshold_uncertainty_score":0.01689786,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2021295150","doi":"10.1366/000370210792434413","title":"Characterization of Fungal-Degraded Lime Wood by X-Ray Diffraction and Cross-Polarization Magic-Angle-Spinning <sup>13</sup>C-Nuclear Magnetic Resonance Spectroscopy","year":2010,"lang":"en","type":"article","venue":"Applied Spectroscopy","topic":"Wood and Agarwood Research","field":"Chemistry","cited_by":20,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Université Laval","funders":"","keywords":"Crystallinity; Crystallite; Magic angle spinning; Cellulose; Lignin; Materials science; Analytical Chemistry (journal); Scanning electron microscope; Magic angle; Chemistry; Nuclear magnetic resonance spectroscopy; Crystallography; Composite material; Organic chemistry","authors":[{"name":"Carmen‐Mihaela Popescu","is_ca":true},{"name":"Per Tomas Larsson","is_ca":true},{"name":"Carmen Mihaela Tibirna","is_ca":true},{"name":"Cornelia Vasile","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.005970738702620021,"gpt":0.2349194261298471,"spread":0.2289486874272271,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002209297,0.0004163695,0.0002700398,0.00065856,0.0002147358,0.0004673031,0.0002641733,0.000324225,0.0009486122],"category_scores_gemma":[0.0003118731,0.0001297947,0.0002445194,0.0005493386,0.0002460815,0.0003377717,0.0001848727,0.0003061459,0.0002184898],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001538319,"about_ca_system_score_gemma":0.0001598392,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001030054,"about_ca_topic_score_gemma":0.001463228,"domain_scores_codex":[0.9998684,0.0000159958,0.00001182224,0.00003291617,0.00004966762,0.0000211394],"domain_scores_gemma":[0.9997277,0.00005789655,0.0000545315,0.00002260133,0.00009570995,0.0000415827],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00006969383,0.00001695724,0.0007264207,0.00004807826,0.000004311909,0.0000767049,0.00002317042,0.00005649024,0.996451,0.00001207821,0.000006506809,0.002508641],"study_design_scores_gemma":[0.000006001259,0.0001589296,0.03402676,0.000009698523,0.00001741494,0.0002383142,0.0001029271,0.0008171108,0.9634313,0.00003336977,0.0011494,0.000008773942],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9907033,0.001377929,0.006248188,0.00002287673,0.000008820732,0.00003232209,0.0007125319,0.00005370188,0.0008403251],"genre_scores_gemma":[0.98641,0.001124198,0.008490507,0.00007051328,0.00001056349,0.00006723068,0.00161666,0.00005239577,0.002158008],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001030054,"threshold_uncertainty_score":0.003173411,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2324746290","doi":"10.1255/jnirs.913","title":"Seeing the Wood in the Trees: Unleashing the Secrets of Wood via near Infrared Spectroscopy","year":2010,"lang":"en","type":"article","venue":"Journal of Near Infrared Spectroscopy","topic":"Wood and Agarwood Research","field":"Chemistry","cited_by":20,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"FPInnovations","funders":"","keywords":"Spectroscopy; Infrared; Infrared spectroscopy; Materials science; Near-infrared spectroscopy; Environmental science; Remote sensing; Optics; Chemistry; Physics; Geology; Organic chemistry","authors":[{"name":"Roger Meder","is_ca":false},{"name":"Thanh Trung","is_ca":true},{"name":"Laurie Schimleck","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.01202366107497777,"gpt":0.2767888713471655,"spread":0.2647652102721877,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001520942,0.0003222411,0.0004292459,0.0005133423,0.001335799,0.002925396,0.0008205777,0.001755527,0.004895744],"category_scores_gemma":[0.002387507,0.0003205766,0.0003081967,0.0003980066,0.004513198,0.007978169,0.001943935,0.00538117,0.00118705],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004736651,"about_ca_system_score_gemma":0.0005347031,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000586136,"about_ca_topic_score_gemma":0.001795564,"domain_scores_codex":[0.9995068,0.0001238134,0.000008485821,0.00005358123,0.0002277837,0.00007954677],"domain_scores_gemma":[0.9989018,0.000619401,0.00006257682,0.0001147153,0.0001517937,0.0001495473],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0008103651,0.0002697605,0.004711336,0.001415396,0.00009626233,0.000708408,0.005694499,0.001541236,0.3196827,0.1474192,0.06925745,0.4483934],"study_design_scores_gemma":[0.00006465483,0.0006136658,0.006586785,0.0006151744,0.0001197004,0.001810672,0.0103942,0.004638983,0.09502382,0.4619012,0.4179626,0.0002684485],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.2716398,0.3263881,0.1375627,0.1262685,0.01012977,0.00008211343,0.0003549305,0.0009998103,0.1265743],"genre_scores_gemma":[0.7921056,0.104996,0.05225869,0.01899561,0.004205425,0.00004037815,0.0001183072,0.0003134043,0.02696662],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004895744,"threshold_uncertainty_score":0.01637793,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2994440022","doi":"10.1016/j.chroma.2019.460775","title":"Chemotyping and identification of protected Dalbergiatimber using gas chromatography quadrupole time of flight mass spectrometry","year":2019,"lang":"en","type":"article","venue":"Journal of Chromatography A","topic":"Wood and Agarwood Research","field":"Chemistry","cited_by":18,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"University of British Columbia; Canadian Forest Service; Natural Resources Canada; Environment and Climate Change Canada","funders":"Canadian Forest Service; Natural Resources Canada; Environment and Climate Change Canada; University of British Columbia; FPInnovations; Australian National University","keywords":"Dalbergia; Chemistry; Species identification; Identification (biology); Chromatography; Mass spectrometry; Gas chromatography; Botany; Biology; Zoology","authors":[{"name":"Dayue Shang","is_ca":true},{"name":"Pamela Brunswick","is_ca":true},{"name":"Jeffrey Yan","is_ca":true},{"name":"Joy Bruno","is_ca":true},{"name":"Isabelle Duchesne","is_ca":true},{"name":"Nathalie Isabel","is_ca":true},{"name":"Graham VanAggelen","is_ca":true},{"name":"Marcus Kim","is_ca":false},{"name":"Philip D. Evans","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.007183431727244352,"gpt":0.2388455883377366,"spread":0.2316621566104923,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000156756,0.0005912658,0.000311794,0.000916407,0.0004177412,0.0004212232,0.0003013185,0.000315705,0.001046996],"category_scores_gemma":[0.0002256572,0.0001361808,0.0002204741,0.000460737,0.0002549323,0.0003065966,0.0002940135,0.0004576323,0.0005424377],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004344876,"about_ca_system_score_gemma":0.0005455253,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00284841,"about_ca_topic_score_gemma":0.006326035,"domain_scores_codex":[0.9997736,0.0000124523,0.00001029273,0.00008504555,0.00006811831,0.00005055417],"domain_scores_gemma":[0.9998813,0.0000157008,0.00002456514,0.00001454718,0.00003643952,0.00002743449],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00006317103,0.00001481228,0.001366601,0.000008784043,0.000003200169,0.00002842786,0.00001846537,0.00002811564,0.9964516,0.00003338977,0.00002294285,0.001960431],"study_design_scores_gemma":[0.00001260649,0.0003624363,0.0678561,0.00001292552,0.00002649003,0.0002550226,0.0001331443,0.001263789,0.9261101,0.0001692779,0.003784735,0.00001338282],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9845412,0.0009050614,0.01001848,0.0001229475,0.00004752455,0.00007671922,0.001648955,0.0002504267,0.00238881],"genre_scores_gemma":[0.9549289,0.001172955,0.03315236,0.0002107856,0.00002277883,0.0001025915,0.002983401,0.00009022194,0.007336055],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00284841,"threshold_uncertainty_score":0.005663633,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4387775258","doi":"10.3390/polym15204147","title":"Quality Control of Thermally Modified Western Hemlock Wood Using Near-Infrared Spectroscopy and Explainable Machine Learning","year":2023,"lang":"en","type":"article","venue":"Polymers","topic":"Wood and Agarwood Research","field":"Chemistry","cited_by":15,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of British Columbia","funders":"","keywords":"Near-infrared spectroscopy; Ranking (information retrieval); Artificial intelligence; Spectroscopy; Machine learning; Materials science; Feature (linguistics); Boosting (machine learning); Computer science; Analytical Chemistry (journal); Environmental science; Pattern recognition (psychology); Remote sensing; Optics; Chemistry; Geology; Physics; Chromatography","authors":[{"name":"Vahid Nasir","is_ca":false},{"name":"Laurence R. Schimleck","is_ca":false},{"name":"Farshid Abdoli","is_ca":false},{"name":"Maria Rashidi","is_ca":false},{"name":"Farrokh Sassani","is_ca":true},{"name":"Stavros Avramidis","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.03527415218095097,"gpt":0.3097141567739806,"spread":0.2744400045930296,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007502054,0.0004083656,0.0003550166,0.0004365695,0.0001538392,0.0005533838,0.0003052142,0.0003600916,0.000309154],"category_scores_gemma":[0.0008230837,0.0001669819,0.0005295433,0.0002544684,0.0002417598,0.0006065487,0.0001880121,0.0003765031,0.000085154],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004414957,"about_ca_system_score_gemma":0.0002474711,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002120265,"about_ca_topic_score_gemma":0.003969963,"domain_scores_codex":[0.999791,0.0000453707,0.000009980908,0.00006020635,0.00007736416,0.00001615088],"domain_scores_gemma":[0.9997359,0.00009454806,0.00006684657,0.00002713659,0.00006772541,0.000007812104],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0003138198,0.0002786158,0.02559438,0.0002238173,0.0001128545,0.0002077712,0.000163749,0.3822348,0.4259997,0.001816869,0.0002784529,0.1627751],"study_design_scores_gemma":[0.000005382952,0.0001450709,0.008935836,0.00000855938,0.00002642171,0.00003194894,0.00002543361,0.9283625,0.06107641,0.001002435,0.0003642307,0.00001594868],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6946712,0.0006185084,0.3029518,0.0001326383,0.00002510041,0.0000497164,0.00008523324,0.0003412033,0.001124646],"genre_scores_gemma":[0.9665554,0.0001876336,0.03268371,0.00002293052,0.000007708927,0.00002004492,0.00008396016,0.00002049481,0.0004181021],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002120265,"threshold_uncertainty_score":0.004215837,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3088305235","doi":"10.3390/f11101043","title":"Wood and Pulping Properties Variation of Acacia crassicarpa A.Cunn. ex Benth. and Sampling Strategies for Accurate Phenotyping","year":2020,"lang":"en","type":"article","venue":"Forests","topic":"Wood and Agarwood Research","field":"Chemistry","cited_by":14,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of British Columbia","funders":"","keywords":"Kraft process; Pulp (tooth); Raw material; Sampling (signal processing); Environmental science; Kraft paper; Pulp and paper industry; Computer science; Biology; Ecology","authors":[{"name":"Gustavo Salgado Martins","is_ca":false},{"name":"Muhammad Yuliarto","is_ca":false},{"name":"Rudine Antes","is_ca":false},{"name":"Sabki","is_ca":false},{"name":"Agung Prasetyo","is_ca":false},{"name":"Faride Unda","is_ca":true},{"name":"Shawn D. Mansfield","is_ca":true},{"name":"Gary R. Hodge","is_ca":false},{"name":"Juan J. Acosta","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.08281452685624652,"gpt":0.2971592778552652,"spread":0.2143447509990187,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005079667,0.0002838538,0.0002793513,0.0009719168,0.0003546307,0.0003567123,0.0003548033,0.0001555245,0.0005515634],"category_scores_gemma":[0.0006178751,0.0001059851,0.0002003402,0.0004742766,0.000163601,0.0001815157,0.0002731895,0.0002812591,0.0001188522],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003482077,"about_ca_system_score_gemma":0.0002107693,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009744783,"about_ca_topic_score_gemma":0.02943338,"domain_scores_codex":[0.9996219,0.00007189267,0.00002522758,0.0001405419,0.0001126061,0.00002783165],"domain_scores_gemma":[0.9992592,0.0002139445,0.0001610703,0.0001014635,0.0001996049,0.00006465164],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0001904402,0.0001853759,0.1712188,0.0001423,0.00008978173,0.00017624,0.0005655326,0.0008892198,0.7594925,0.0001144571,0.0001213712,0.06681396],"study_design_scores_gemma":[0.000006611379,0.0001240562,0.9818004,0.00001026452,0.00004951248,0.0001490519,0.0001498321,0.001617696,0.01525654,0.00003908901,0.0007868703,0.00001012001],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9967146,0.0002206069,0.002086168,0.00000762225,0.000002406253,0.00004750994,0.000332369,0.00003347712,0.0005553056],"genre_scores_gemma":[0.9919086,0.00009991066,0.006498584,0.00002192999,0.000002872622,0.00007503208,0.001011662,0.00001894644,0.0003625397],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009744783,"threshold_uncertainty_score":0.01937616,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2135832881","doi":"10.1007/s00226-012-0468-9","title":"Rapid spectroscopic separation of three Canadian softwoods","year":2012,"lang":"en","type":"article","venue":"Wood Science and Technology","topic":"Wood and Agarwood Research","field":"Chemistry","cited_by":13,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"FPInnovations","keywords":"Calibration; Softwood; Near-infrared spectroscopy; Principal component analysis; Wavelength; Spectroscopy; Analytical Chemistry (journal); Data set; Spectral line; Materials science; Remote sensing; Mathematics; Chemistry; Optics; Chromatography; Geology; Physics; Statistics; Composite material; Optoelectronics","authors":[{"name":"Benjamin Dawson‐Andoh","is_ca":false},{"name":"Oluwatosin E. Adedipe","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.01905242270328462,"gpt":0.2891288343619212,"spread":0.2700764116586366,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000316839,0.0006139547,0.0003514008,0.001712735,0.003350702,0.001256004,0.0007096332,0.0004252262,0.003670003],"category_scores_gemma":[0.0004088592,0.000199605,0.0001707158,0.001090578,0.0005426301,0.0004328134,0.0005421108,0.0009499649,0.0004409624],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005309082,"about_ca_system_score_gemma":0.006784367,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.6694943,"about_ca_topic_score_gemma":0.853161,"domain_scores_codex":[0.9996638,0.000007350717,0.000004540088,0.00006234978,0.0001492602,0.0001126531],"domain_scores_gemma":[0.9996096,0.00003396171,0.00001495576,0.000009232854,0.0002444366,0.00008776854],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0005622638,0.00006971034,0.005176104,0.0001108693,0.0000262265,0.0001714321,0.0006773496,0.0003918378,0.9537466,0.0009486922,0.001236273,0.03688264],"study_design_scores_gemma":[0.0000677884,0.0002812617,0.118299,0.00003797467,0.0001048061,0.0002694163,0.002560866,0.002749741,0.840988,0.0004761264,0.03406565,0.00009934181],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9798691,0.001274259,0.003947172,0.0002235069,0.00005991783,0.0001013869,0.0007301589,0.00012333,0.01367128],"genre_scores_gemma":[0.9676495,0.001194037,0.008347082,0.0001980438,0.00001627891,0.0000394554,0.0008761493,0.00007702746,0.0216023],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3305057,"threshold_uncertainty_score":0.6649042,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2013188964","doi":"10.1515/hf.2009.089","title":"Reconstruction of 3D images of internal log characteristics by means of successive 2D log computed tomography images","year":2009,"lang":"en","type":"article","venue":"Holzforschung","topic":"Wood and Agarwood Research","field":"Chemistry","cited_by":13,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"FPInnovations; University of New Brunswick","funders":"","keywords":"Computed tomography; Artificial intelligence; Maple; Mathematics; Computer science; Pattern recognition (psychology); Computer vision; Biology; Botany; Medicine; Radiology","authors":[{"name":"Qiang Wei","is_ca":true},{"name":"Shu Yin Zhang","is_ca":true},{"name":"Ying Hei Chui","is_ca":true},{"name":"Brigitte Leblon","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.008431576020990029,"gpt":0.2523439729420697,"spread":0.2439123969210796,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002905997,0.0005270962,0.0002509041,0.001451432,0.0001179194,0.0007690119,0.0002162649,0.0003107441,0.001910229],"category_scores_gemma":[0.0007853302,0.0003993791,0.0003130895,0.000942207,0.0002400281,0.0004329091,0.0003117037,0.0003971932,0.0003675957],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000182534,"about_ca_system_score_gemma":0.0004231066,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00116243,"about_ca_topic_score_gemma":0.002450332,"domain_scores_codex":[0.9998901,0.00001406809,0.000006896938,0.0000155021,0.00005826141,0.00001510642],"domain_scores_gemma":[0.9996884,0.00009963797,0.00004281458,0.00005438031,0.00009341305,0.00002142237],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004611614,0.00009318595,0.01479507,0.0003088416,0.0000720149,0.001265397,0.0004109495,0.0717397,0.7255247,0.001678483,0.001342578,0.182308],"study_design_scores_gemma":[0.00005491258,0.0002324082,0.06553403,0.00005027657,0.0001026443,0.004114785,0.0005081329,0.5782253,0.3423437,0.001493039,0.007190764,0.0001499702],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5170782,0.000285576,0.4787472,0.000153768,0.000042519,0.00009848135,0.0006299354,0.001102179,0.001862154],"genre_scores_gemma":[0.6946661,0.0004386561,0.3030279,0.00003844444,0.00002027958,0.0000558364,0.0004724143,0.0001424139,0.001137913],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001910229,"threshold_uncertainty_score":0.006390393,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4281560036","doi":"10.1139/cjfr-2022-0077","title":"Towards sustainable North American wood product value chains, part 2: computer vision identification of ring-porous hardwoods","year":2022,"lang":"en","type":"article","venue":"Canadian Journal of Forest Research","topic":"Wood and Agarwood Research","field":"Chemistry","cited_by":9,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false},"ca_institutions":"","funders":"U.S. Department of Agriculture; U.S. Department of State","keywords":"Hardwood; Artificial intelligence; Identification (biology); Softwood; Machine learning; Porosity; Computer science; Pulp and paper industry; Wood industry; Environmental science; Agricultural engineering; Pattern recognition (psychology); Materials science; Engineering; Botany; Composite material; Forestry; Geography; Biology","authors":[{"name":"Prabu Ravindran","is_ca":false},{"name":"Adam C. Wade","is_ca":false},{"name":"Frank C. Owens","is_ca":false},{"name":"Rubin Shmulsky","is_ca":false},{"name":"Alex C. Wiedenhoeft","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.02411249853117978,"gpt":0.3063111182411508,"spread":0.282198619709971,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001719611,0.0007103237,0.0002867064,0.00144052,0.0006713952,0.002469016,0.0008384862,0.0006768858,0.002982965],"category_scores_gemma":[0.001483931,0.0003016666,0.0004037678,0.001192567,0.0006868669,0.002943942,0.001316658,0.001086373,0.001118189],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001507296,"about_ca_system_score_gemma":0.002305597,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03611987,"about_ca_topic_score_gemma":0.07700243,"domain_scores_codex":[0.9995698,0.0000771054,0.0000106303,0.00008424986,0.0001891537,0.00006909173],"domain_scores_gemma":[0.9991788,0.0001253655,0.0001037495,0.00009036706,0.0004445707,0.00005712989],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001173899,0.0001896399,0.0386082,0.0002255365,0.00007360401,0.0001219379,0.0004896932,0.1010322,0.02344962,0.01810458,0.02669113,0.7908965],"study_design_scores_gemma":[0.00001220008,0.000109141,0.03667546,0.0002348152,0.00003988606,0.0001228472,0.001317558,0.8462011,0.02073743,0.03753734,0.05694789,0.00006439447],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2686653,0.00220556,0.6873516,0.003603077,0.0001638746,0.0002584242,0.001083159,0.002237932,0.03443112],"genre_scores_gemma":[0.6573793,0.002071287,0.3248877,0.0005113382,0.00005026131,0.0001191181,0.001750414,0.0002789757,0.01295166],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9638801,"threshold_uncertainty_score":0.07181925,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W6948475182","doi":"10.5061/dryad.238b2","title":"Data from: The unique ecology of human predators","year":2015,"lang":"en","type":"dataset","venue":"Data Archiving and Networked Services (DANS)","topic":"Wood and Agarwood Research","field":"Chemistry","cited_by":8,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Victoria","funders":"","keywords":"Predation; Population; Evolutionary ecology; Apex predator; Functional ecology; Population ecology","authors":[],"retraction":null,"screen_n_in":null,"score":{"opus":0.0636486424753353,"gpt":0.3249023798357877,"spread":0.2612537373604524,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00109524,0.00177573,0.001234083,0.003316145,0.0006664146,0.002589488,0.00234555,0.001599982,0.06543062],"category_scores_gemma":[0.008422705,0.0005550534,0.0009445416,0.006847071,0.0004196333,0.001390373,0.002368357,0.001620813,0.07617788],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00149837,"about_ca_system_score_gemma":0.002754115,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03247666,"about_ca_topic_score_gemma":0.0516701,"domain_scores_codex":[0.9989086,0.0001398132,0.0001768861,0.0003070848,0.0003154504,0.0001521532],"domain_scores_gemma":[0.9975355,0.0006225036,0.0004326468,0.0004814016,0.0006753657,0.0002527297],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.00005758331,0.0000141142,0.00199935,0.001237855,0.00004065302,0.00002988967,0.00005686871,0.0002488442,0.0001247486,0.0008015569,0.9919151,0.003473472],"study_design_scores_gemma":[0.0001564922,0.000008130713,0.008328916,0.0005041994,0.00003075765,0.00005123013,0.0001000439,0.000240373,0.0002667394,0.00138987,0.9888966,0.00002664174],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001502578,0.00008380991,0.00005530276,0.00007880506,0.00001317182,0.000006298681,0.9986999,0.0001732448,0.0007391774],"genre_scores_gemma":[0.0008194357,0.0001094984,0.0003067573,0.00004624209,0.000005796898,0.00006622056,0.9979079,0.00007016726,0.0006679396],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.06543062,"threshold_uncertainty_score":0.2188872,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W6949095370","doi":"10.5281/zenodo.10030166","title":"Scale-adjusted metrics of scientific collaboration","year":2011,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Wood and Agarwood Research","field":"Chemistry","cited_by":7,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"","keywords":"Normalization (sociology); Function (biology); Preference; Index (typography); Comparability","authors":[],"retraction":null,"screen_n_in":null,"score":{"opus":0.06473270293658599,"gpt":0.2505745339732636,"spread":0.1858418310366776,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch","bibliometrics"],"consensus_categories":[],"category_scores_codex":[0.00833628,0.0006063264,0.0006968686,0.01250868,0.000791705,0.002471095,0.000933496,0.0007552116,0.002700773],"category_scores_gemma":[0.06723448,0.0002299193,0.0008435626,0.01399475,0.001211884,0.006054118,0.001931368,0.00076377,0.0006149749],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00147146,"about_ca_system_score_gemma":0.0007444967,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001403138,"about_ca_topic_score_gemma":0.001248812,"domain_scores_codex":[0.9888714,0.003619962,0.001396728,0.001338946,0.004296598,0.0004764023],"domain_scores_gemma":[0.959482,0.01996617,0.007439111,0.005535427,0.006118522,0.001458883],"domain_codex":null,"domain_gemma":"evaluation","domain_candidate":"evaluation","domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0007520719,0.0002942387,0.2551239,0.0008807952,0.001012858,0.0004216709,0.005192989,0.0576319,0.01487742,0.1971893,0.007909005,0.4587139],"study_design_scores_gemma":[0.00007217363,0.001023442,0.4038618,0.0001821145,0.0002206246,0.001368978,0.00488066,0.2335554,0.009280883,0.3118517,0.03314427,0.0005579058],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.4683188,0.001273642,0.5002167,0.0005266691,0.0002042282,0.0004169114,0.00382983,0.001025125,0.02418817],"genre_scores_gemma":[0.893913,0.000306727,0.1022841,0.00004508004,0.00008776267,0.0004037659,0.001462168,0.0001006642,0.001396725],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9916637,"threshold_uncertainty_score":0.04408699,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2114519351","doi":"10.1109/ccece.2007.110","title":"Neural Networks for Color Image Segmentation: Application to Sapwood Assessment","year":2007,"lang":"en","type":"article","venue":"","topic":"Wood and Agarwood Research","field":"Chemistry","cited_by":7,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Université Laval","funders":"Université Laval","keywords":"Artificial neural network; Artificial intelligence; Process (computing); Computer science; Maple; Segmentation; Image segmentation; Deep neural networks; Image (mathematics); Computer vision; Pattern recognition (psychology); Botany","authors":[{"name":"Adel Ziadi","is_ca":true},{"name":"Frédéric Ntawiniga","is_ca":true},{"name":"Xavier Maldague","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.01488828749883239,"gpt":0.3548233465057293,"spread":0.3399350590068969,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005882888,0.0007871051,0.0004899277,0.001048493,0.0003256041,0.000583688,0.000499237,0.001020358,0.002644323],"category_scores_gemma":[0.001330937,0.0003132913,0.0003303747,0.0009568448,0.0003234701,0.0005406674,0.0003220694,0.0005712133,0.0005998456],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000562027,"about_ca_system_score_gemma":0.000289786,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005331848,"about_ca_topic_score_gemma":0.005217796,"domain_scores_codex":[0.9997943,0.00005913475,0.00001057698,0.00004125134,0.00007006638,0.0000246831],"domain_scores_gemma":[0.9995251,0.0002644077,0.00003920636,0.00002605666,0.0001259419,0.00001937534],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0003031778,0.0001257134,0.001598657,0.0001770709,0.00007558902,0.0002230085,0.0001116193,0.2272438,0.06829023,0.002865106,0.002051128,0.6969348],"study_design_scores_gemma":[0.000009345108,0.00003853146,0.0009321615,0.00001284679,0.00001494437,0.00006457158,0.00001726003,0.9778011,0.01797908,0.001707795,0.001407072,0.00001525074],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04192998,0.001234379,0.9511142,0.0002891535,0.00007449122,0.00007717812,0.00008855167,0.002176747,0.003015271],"genre_scores_gemma":[0.3978554,0.001224169,0.5932634,0.0001348096,0.00007870532,0.0001052174,0.0001259775,0.000225176,0.006987181],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005331848,"threshold_uncertainty_score":0.01060164,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4385858746","doi":"10.22382/wfs-2023-07","title":"COMPARING GC×GC-TOFMS-BASED METABOLOMIC PROFILING AND WOOD ANATOMY FOR FORENSIC IDENTIFICATION OF FIVE MELIACEAE (MAHOGANY) SPECIES","year":2023,"lang":"en","type":"article","venue":"Wood and Fiber Science","topic":"Wood and Agarwood Research","field":"Chemistry","cited_by":6,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Université Laval; University of Alberta; Natural Resources Canada; Canadian Forest Service","funders":"","keywords":"Swietenia macrophylla; Khaya; Biology; Meliaceae; Snag; Botany; Ecology","authors":[{"name":"Isabelle Duchesne","is_ca":true},{"name":"Dikshya Dixit Lamichhane","is_ca":false},{"name":"Ryan P. Dias","is_ca":false},{"name":"A. Paulina de la Mata","is_ca":false},{"name":"Martin Williams","is_ca":false},{"name":"Manuel Lamothe","is_ca":false},{"name":"James J. Harynuk","is_ca":false},{"name":"Nathalie Isabel","is_ca":true},{"name":"Alain Cloutier","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.03435370089317142,"gpt":0.2985749791730768,"spread":0.2642212782799054,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001969881,0.0004014448,0.0001579766,0.001231429,0.0002443024,0.000370621,0.0001575399,0.0003588278,0.0005236521],"category_scores_gemma":[0.000296507,0.0001148098,0.000278504,0.0006205649,0.0002421095,0.0002637943,0.0002676083,0.0001872433,0.0001312526],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001223247,"about_ca_system_score_gemma":0.0001309768,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001107763,"about_ca_topic_score_gemma":0.003413704,"domain_scores_codex":[0.9998475,0.00001900687,0.00001105976,0.00006742562,0.00003143481,0.0000234957],"domain_scores_gemma":[0.999905,0.00002148988,0.00002432078,0.000007070652,0.0000307025,0.00001137665],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002367854,0.00006258472,0.02223924,0.0001693563,0.00006827651,0.0001522989,0.000313798,0.0001632157,0.9579614,0.0001007612,0.00007294216,0.01845929],"study_design_scores_gemma":[0.0000235074,0.001025967,0.5583969,0.00007203774,0.0003511105,0.001554475,0.001729384,0.005764078,0.4227751,0.0003943766,0.007840502,0.0000725835],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9927044,0.001541683,0.003450592,0.00006059003,0.00002192008,0.00004283679,0.000816607,0.0000371401,0.001324367],"genre_scores_gemma":[0.9852678,0.0007924148,0.01150663,0.0001188119,0.00001306786,0.00005291985,0.0008979274,0.00001312677,0.001337341],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001231429,"threshold_uncertainty_score":0.00220263,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3119816308","doi":"10.1139/cjfr-2020-0416","title":"Identification of North American softwoods via machine-learning","year":2021,"lang":"en","type":"article","venue":"Canadian Journal of Forest Research","topic":"Wood and Agarwood Research","field":"Chemistry","cited_by":5,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false},"ca_institutions":"","funders":"","keywords":"Overfitting; Artificial intelligence; Convolutional neural network; Softwood; Pixel; Computer science; Pattern recognition (psychology); Pinus pinaster; Data set; Training set; Initialization; Mathematics; Artificial neural network; Engineering","authors":[{"name":"Dercílio Júnior Verly Lopes","is_ca":false},{"name":"Gabrielly dos Santos Bobadilha","is_ca":false},{"name":"Greg W. Burgreen","is_ca":false},{"name":"Edward D. Entsminger","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.02904311413289832,"gpt":0.3162362375941895,"spread":0.2871931234612912,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001015143,0.000437544,0.0002431204,0.001034274,0.0003844603,0.0006931369,0.0004562655,0.0004190105,0.001099038],"category_scores_gemma":[0.0008895051,0.0001570833,0.0002759813,0.0005155464,0.0002059234,0.0009008371,0.0004069205,0.0002395254,0.0008309551],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004373011,"about_ca_system_score_gemma":0.0004049107,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009733406,"about_ca_topic_score_gemma":0.03765914,"domain_scores_codex":[0.9996089,0.00007016926,0.00001635679,0.0001503028,0.0001128872,0.00004149817],"domain_scores_gemma":[0.9994972,0.0001289589,0.00006317157,0.00006590501,0.0002156751,0.00002909806],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004893159,0.0002504361,0.1823903,0.0002265174,0.000118396,0.0004431749,0.0003185096,0.04904725,0.2567407,0.001144804,0.003357893,0.5054727],"study_design_scores_gemma":[0.000009849688,0.0001404115,0.1561247,0.0000418981,0.00005752869,0.0004372018,0.0003024089,0.7279512,0.1084086,0.00113939,0.005336274,0.00005050676],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9149868,0.0005338722,0.07892123,0.0001555169,0.00005071323,0.00004644791,0.0004572011,0.0006962806,0.004151894],"genre_scores_gemma":[0.945492,0.000161459,0.05100444,0.00005268148,0.00001085251,0.00001642182,0.0006342132,0.00002185886,0.002606105],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9902666,"threshold_uncertainty_score":0.01935351,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4399247298","doi":"10.3389/fpls.2024.1413215","title":"Visible/near-infrared hyperspectral imaging combined with machine learning for identification of ten Dalbergia species","year":2024,"lang":"en","type":"article","venue":"Frontiers in Plant Science","topic":"Wood and Agarwood Research","field":"Chemistry","cited_by":5,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of British Columbia","funders":"Government of Jiangsu Province","keywords":"Hyperspectral imaging; Infrared; Identification (biology); Remote sensing; Computer science; Botany; Artificial intelligence; Environmental science; Biology; Optics; Physics; Geography","authors":[{"name":"Zhenan Chen","is_ca":true},{"name":"Xiaoming Xue","is_ca":false},{"name":"Haoqi Wu","is_ca":true},{"name":"Handong Gao","is_ca":false},{"name":"Guangyu Wang","is_ca":true},{"name":"Geyi Ni","is_ca":false},{"name":"Tianyi Cao","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.008818620745754598,"gpt":0.241597192246119,"spread":0.2327785715003644,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005416803,0.0004485575,0.0002902378,0.001536253,0.0003584566,0.0007700678,0.0004707957,0.0002895948,0.0009129651],"category_scores_gemma":[0.0005361931,0.0002055691,0.0004435025,0.0006024193,0.0002477549,0.0007113388,0.0004016104,0.0003762532,0.000391817],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005486133,"about_ca_system_score_gemma":0.0004913229,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006985748,"about_ca_topic_score_gemma":0.01683816,"domain_scores_codex":[0.9998019,0.0000274865,0.00001290088,0.00008615707,0.00004811836,0.00002346019],"domain_scores_gemma":[0.9998059,0.00004485673,0.00004309709,0.00001741775,0.00006609219,0.0000225763],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0006178148,0.0005430697,0.2284273,0.0004124119,0.000202969,0.0002847247,0.0004915752,0.03039967,0.261258,0.0008790547,0.001432274,0.4750512],"study_design_scores_gemma":[0.00002957772,0.0003523773,0.3234558,0.00009145059,0.0002609748,0.0002665452,0.0005951862,0.5812633,0.08693943,0.002041629,0.004623758,0.00007999125],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9533724,0.0009052756,0.03999249,0.0001964804,0.00004818001,0.00006976916,0.000451465,0.000487654,0.004476247],"genre_scores_gemma":[0.9578263,0.0002364262,0.04007038,0.00004630114,0.00001075414,0.00002645963,0.0003332408,0.00002060776,0.001429709],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006985748,"threshold_uncertainty_score":0.01389021,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4389665291","doi":"10.1080/17480272.2023.2293177","title":"Wood-species identification based on terahertz spectral data augmentation and pseudo-label guided deep clustering","year":2023,"lang":"en","type":"article","venue":"Wood Material Science and Engineering","topic":"Wood and Agarwood Research","field":"Chemistry","cited_by":4,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of British Columbia","funders":"","keywords":"Autoencoder; Cluster analysis; Discriminative model; Artificial intelligence; Pattern recognition (psychology); Computer science; Deep learning; Identification (biology); Machine learning; Mathematics; Biology","authors":[{"name":"Yuan Wang","is_ca":false},{"name":"Zhigang Wang","is_ca":false},{"name":"Yi-Hao He","is_ca":false},{"name":"Stavros Avramidis","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.04481481709318126,"gpt":0.2903728878742032,"spread":0.245558070781022,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000494723,0.0006076808,0.0003880069,0.0006965429,0.0002983712,0.0004970533,0.0009255718,0.0006040101,0.0007916718],"category_scores_gemma":[0.0007582328,0.0003233508,0.0006999726,0.0004902713,0.0005622417,0.001206228,0.0007994815,0.0007899605,0.0003504672],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004849856,"about_ca_system_score_gemma":0.00056345,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003050886,"about_ca_topic_score_gemma":0.006488322,"domain_scores_codex":[0.9997839,0.00003361848,0.000007565568,0.00008733052,0.00005446751,0.00003321005],"domain_scores_gemma":[0.9997297,0.00007435681,0.00003801579,0.00005820703,0.00008254775,0.00001712681],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002623597,0.0001960207,0.00547758,0.000114962,0.00008800942,0.0001077056,0.0002227019,0.5678861,0.1283816,0.0121018,0.001545413,0.2836159],"study_design_scores_gemma":[0.000001969568,0.00001189047,0.0005172527,0.000002621275,0.000004320178,0.00001770011,0.00001151674,0.988624,0.008808617,0.001648408,0.000344594,0.000007117867],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08125948,0.0001003015,0.9167321,0.00006925302,0.00002031311,0.00002771356,0.00009556726,0.0005728018,0.001122435],"genre_scores_gemma":[0.644801,0.0001238267,0.3506364,0.0001117977,0.00001515425,0.00007879919,0.00058667,0.0001211199,0.003525286],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003050886,"threshold_uncertainty_score":0.006066263,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4388485953","doi":"10.1080/09540105.2023.2265688","title":"The enhancement of bioactive phytochemicals in agarwood leaves by post-harvest application using yeast extract elicitors and evaluation of their bioactivities","year":2023,"lang":"en","type":"article","venue":"Food and Agricultural Immunology","topic":"Wood and Agarwood Research","field":"Chemistry","cited_by":4,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"","funders":"Faculty of Pharmacy and Pharmaceutical Sciences, University of Alberta; Khon Kaen University","keywords":"Agarwood; Yeast; Food science; Chemistry; Elicitor; Traditional medicine; Bioactive compound; Biology; Biochemistry; Enzyme; Medicine","authors":[{"name":"Rattanathorn Choonong","is_ca":false},{"name":"Jakkrit Jabsanthia","is_ca":false},{"name":"Varinda Waewaram","is_ca":false},{"name":"Khunkhang Butdapheng","is_ca":false},{"name":"Boonchoo Sritularak","is_ca":false},{"name":"Waraporn Putalun","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.02348450298438428,"gpt":0.2802395376098251,"spread":0.2567550346254408,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007114297,0.0004203572,0.0002153544,0.0001740313,0.000104761,0.0001913207,0.00009076647,0.0001546843,0.0007785633],"category_scores_gemma":[0.00004750704,0.00007958212,0.0002955995,0.000149409,0.00008919772,0.0002115543,0.000139312,0.0004332361,0.0001278642],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001169059,"about_ca_system_score_gemma":0.0001155629,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003786475,"about_ca_topic_score_gemma":0.00100519,"domain_scores_codex":[0.9999564,0.000005711459,0.000003884475,0.00001005943,0.00001301435,0.00001094409],"domain_scores_gemma":[0.9999573,0.000006857157,0.00001216357,0.000003977628,0.000009093141,0.00001058481],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00004819677,0.00001437644,0.00006549244,0.00003663154,0.000001699151,0.0000171338,0.000005349413,0.00001068145,0.9992341,0.00000850692,0.000004183327,0.0005536672],"study_design_scores_gemma":[0.000004565689,0.0002520896,0.004173615,0.000006688861,0.00001021339,0.00006044862,0.00002942534,0.0001096441,0.9947616,0.0000135195,0.000575747,0.000002417232],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9940245,0.001928756,0.002591938,0.00005665881,0.00001703068,0.00003402618,0.0003620391,0.00003943761,0.0009455621],"genre_scores_gemma":[0.9914186,0.001337062,0.003644826,0.00007084267,0.000007465125,0.0000361969,0.0005789202,0.00001355283,0.002892463],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0007785633,"threshold_uncertainty_score":0.002604544,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4285803070","doi":"10.1139/gen-2022-0003","title":"Genome-wide investigation and expression analysis of the AP2/ERF family for selection of agarwood-related genes in <i>Aquilaria sinensis</i> (Lour.) Gilg","year":2022,"lang":"en","type":"article","venue":"Genome","topic":"Wood and Agarwood Research","field":"Chemistry","cited_by":4,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false},"ca_institutions":"","funders":"National Key Research and Development Program of China","keywords":"Agarwood; Biology; Methyl jasmonate; Gene; Genome; Genetics; Gene family; Subfamily","authors":[{"name":"Mengjun Xiao","is_ca":false},{"name":"Ya‐Nan Feng","is_ca":false},{"name":"Yongsheng Xu","is_ca":false},{"name":"Mei Rong","is_ca":false},{"name":"Yang Liu","is_ca":false},{"name":"Jiemei Jiang","is_ca":false},{"name":"Cuicui Yu","is_ca":false},{"name":"Zhihui Gao","is_ca":false},{"name":"Jianhe Wei","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.01515170760273131,"gpt":0.2290812274577222,"spread":0.2139295198549909,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001704676,0.000241439,0.0003197149,0.0005346292,0.0002367081,0.0002171935,0.0001604904,0.0002045744,0.0008109531],"category_scores_gemma":[0.00008779478,0.0001132736,0.0004596029,0.0005439176,0.0001286539,0.0001003172,0.0002049604,0.0002640764,0.0002297758],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001465847,"about_ca_system_score_gemma":0.0001431759,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001034647,"about_ca_topic_score_gemma":0.001555188,"domain_scores_codex":[0.9999021,0.000007482976,0.000009713252,0.00004564601,0.00002114265,0.00001397074],"domain_scores_gemma":[0.9998986,0.00002010459,0.00003317122,0.000007684182,0.00002005978,0.00002046268],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001510473,0.00003762347,0.01199408,0.00009839563,0.00003090816,0.0001246999,0.00009280257,0.00004786648,0.9835776,0.00003979799,0.00008729259,0.003717809],"study_design_scores_gemma":[0.0000710373,0.0003415134,0.8970132,0.00002379812,0.0001770147,0.00111802,0.0004005324,0.002538446,0.09217124,0.0001017616,0.006017992,0.00002532493],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9966689,0.0005383338,0.0008448758,0.00003549511,0.000006013576,0.00001624003,0.001502939,0.0000367877,0.0003504229],"genre_scores_gemma":[0.9872231,0.0003839157,0.00192774,0.0001403377,0.00001014013,0.0000501938,0.007821346,0.00002422552,0.002418964],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001034647,"threshold_uncertainty_score":0.002712905,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3213715497","doi":"10.18280/ria.350503","title":"A Precision Agricultural Application: Manggis Fruit Classification Using Hybrid Deep Learning","year":2021,"lang":"en","type":"article","venue":"Revue d intelligence artificielle","topic":"Wood and Agarwood Research","field":"Chemistry","cited_by":4,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false},"ca_institutions":"","funders":"","keywords":"Artificial intelligence; Computer science; Initialization; Convolutional neural network; Pattern recognition (psychology); Convolution (computer science); Contextual image classification; Artificial neural network; Machine learning; Image (mathematics)","authors":[{"name":"Putra Sumari","is_ca":false},{"name":"Wan Muhammad Azimuddin Wan Ahmad","is_ca":false},{"name":"Faris Hadi","is_ca":false},{"name":"Muhammad Mazlan","is_ca":false},{"name":"Nur Anis Liyana","is_ca":false},{"name":"Rotimi-Williams Bello","is_ca":false},{"name":"Ahmad Sufril Azlan Mohamed","is_ca":false},{"name":"Abdullah Zawawi Talib","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.05790009359898297,"gpt":0.3074115263600595,"spread":0.2495114327610766,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000289881,0.0008509398,0.000524206,0.001005737,0.0002885217,0.0006569051,0.0007927536,0.0009003518,0.001981367],"category_scores_gemma":[0.0003245123,0.0001784745,0.0005628196,0.0009520199,0.000215792,0.0007712612,0.0005087114,0.0004174722,0.0009726505],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006015692,"about_ca_system_score_gemma":0.0004124396,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008461687,"about_ca_topic_score_gemma":0.01408853,"domain_scores_codex":[0.9997533,0.00001795439,0.00001184293,0.0001040431,0.00006337248,0.0000494807],"domain_scores_gemma":[0.9998513,0.00002950198,0.00001444242,0.00002732773,0.00005756509,0.00001986693],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0009104359,0.0005742751,0.0429562,0.0006349651,0.000299283,0.001718728,0.0002247303,0.07031444,0.1083109,0.001656968,0.03648169,0.7359174],"study_design_scores_gemma":[0.00006817487,0.0003706468,0.05198158,0.0000844786,0.0001018107,0.0006268067,0.000458422,0.8446026,0.07466988,0.002604371,0.0243442,0.00008704785],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7272793,0.002451773,0.2230847,0.001576313,0.0005759238,0.000352256,0.009207846,0.01547167,0.02000013],"genre_scores_gemma":[0.837173,0.000553932,0.1376835,0.000335479,0.0000923851,0.00009258938,0.009626661,0.0001531916,0.01428916],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008461687,"threshold_uncertainty_score":0.01682484,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4385852252","doi":"10.22382/wfs-2023-04","title":"DISTINGUISHING NATIVE AND PLANTATION-GROWN MAHOGANY (SWIETENIA MACROPHYLLA) TIMBER USING CHROMATOGRAPHY AND HIGH-RESOLUTION QUADRUPOLE TIME-OF-FLIGHT MASS SPECTROMETRY","year":2023,"lang":"en","type":"article","venue":"Wood and Fiber Science","topic":"Wood and Agarwood Research","field":"Chemistry","cited_by":4,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Environment and Climate Change Canada; University of British Columbia","funders":"Environment and Climate Change Canada; FPInnovations; Agilent Technologies","keywords":"Swietenia macrophylla; Hardwood; High resolution; Chemistry; Mass spectrometry; Botany; Horticulture; Environmental science; Chromatography; Biology; Geography; Archaeology","authors":[{"name":"Joseph Doh Wook Kim","is_ca":true},{"name":"Pamela Brunswick","is_ca":true},{"name":"Dayue Shang","is_ca":true},{"name":"Philip D. Evans","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.01307625205126823,"gpt":0.2595521965439819,"spread":0.2464759444927137,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001437869,0.0004928117,0.0001909038,0.0008920659,0.000302543,0.0003510272,0.0001534457,0.000288773,0.0004756292],"category_scores_gemma":[0.0002449828,0.00012491,0.0002249123,0.0003912814,0.0002234181,0.0003030231,0.0002286608,0.0002079699,0.0001527364],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001430434,"about_ca_system_score_gemma":0.0002489414,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004263007,"about_ca_topic_score_gemma":0.01860187,"domain_scores_codex":[0.9998857,0.000007260795,0.00001121502,0.00003886322,0.00003382141,0.00002315092],"domain_scores_gemma":[0.9998648,0.00002944408,0.00004150943,0.000008403768,0.00003404945,0.00002178471],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001313318,0.00003713796,0.03291314,0.000113203,0.00002983988,0.0002704795,0.0001816818,0.00006546777,0.9548936,0.00003451811,0.00004972325,0.01127988],"study_design_scores_gemma":[0.00001114066,0.0003140481,0.8128752,0.00002858749,0.0001066442,0.001268727,0.0006474204,0.001718831,0.1802629,0.00007946607,0.002644608,0.00004250702],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9964227,0.0006228627,0.001712442,0.00002281224,0.00000898602,0.0000265959,0.0004241679,0.0000269969,0.0007323395],"genre_scores_gemma":[0.9843017,0.0008572136,0.01215284,0.0001070517,0.00001166228,0.00004242449,0.001065487,0.00001430814,0.001447328],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004263007,"threshold_uncertainty_score":0.008476377,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4400358528","doi":"10.1038/s41598-023-50739-4","title":"An appearance quality classification method for Auricularia auricula based on deep learning","year":2024,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Wood and Agarwood Research","field":"Chemistry","cited_by":3,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Ministry of Agriculture","funders":"","keywords":"Auricularia; Artificial intelligence; Computer science; Quality (philosophy); Traditional medicine; Biology; Food science; Medicine","authors":[{"name":"Li Yang","is_ca":false},{"name":"Jiajun Hu","is_ca":false},{"name":"Haiyun Wu","is_ca":false},{"name":"Yongqi Wei","is_ca":false},{"name":"Huiyong Shan","is_ca":false},{"name":"Xin Song","is_ca":false},{"name":"Xiuping Hua","is_ca":false},{"name":"Wei Xu","is_ca":false},{"name":"Yongcheng Jiang","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.04356492902971346,"gpt":0.3876340562052972,"spread":0.3440691271755838,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004490983,0.0006425992,0.0006133739,0.001438053,0.0002467696,0.0007458374,0.0006033415,0.0006021251,0.00120074],"category_scores_gemma":[0.001141311,0.0002472126,0.0009730972,0.0005796999,0.0002760236,0.001130556,0.0006694615,0.0007255106,0.0005344302],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006201222,"about_ca_system_score_gemma":0.0004321601,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005264067,"about_ca_topic_score_gemma":0.004945005,"domain_scores_codex":[0.999559,0.00003111034,0.00003131328,0.0001094137,0.0002044402,0.00006465636],"domain_scores_gemma":[0.9994661,0.00005766817,0.00006089381,0.00005467963,0.0003208333,0.00003974622],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0003041345,0.00008764305,0.01283057,0.0001811402,0.0001174427,0.0002709027,0.00009331904,0.03062161,0.09212928,0.001409161,0.004982735,0.856972],"study_design_scores_gemma":[0.00002350207,0.0001103321,0.01504831,0.00002781086,0.0001294078,0.0005487303,0.00006465441,0.9396493,0.0394504,0.001377661,0.003524474,0.00004544513],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09754451,0.001394761,0.8942765,0.0002738334,0.000165705,0.00009791132,0.0001968546,0.002258373,0.003791468],"genre_scores_gemma":[0.8254965,0.001360479,0.1641634,0.000237924,0.0001279819,0.00008129633,0.0007164076,0.0001889256,0.007627021],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005264067,"threshold_uncertainty_score":0.01046687,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4409665375","doi":"10.1007/s00226-025-01657-3","title":"Classification of wood species in trade using metabolomic profiling by GC×GC-TOFMS","year":2025,"lang":"en","type":"article","venue":"Wood Science and Technology","topic":"Wood and Agarwood Research","field":"Chemistry","cited_by":3,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"Natural Resources Canada; Canadian Forest Service; The Metabolomics Innovation Centre","funders":"Canadian Forest Service","keywords":"Gas chromatography–mass spectrometry; Metabolomics; Profiling (computer programming); Chemistry; Chromatography; Mass spectrometry; Computer science","authors":[{"name":"Ryan P. Dias","is_ca":true},{"name":"Seo Lin Nam","is_ca":true},{"name":"A. Paulina de la Mata","is_ca":true},{"name":"Martin Williams","is_ca":true},{"name":"Isabelle Duchesne","is_ca":true},{"name":"Manuel Lamothe","is_ca":true},{"name":"Nathalie Isabel","is_ca":true},{"name":"James J. Harynuk","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.02794367896908975,"gpt":0.2999066931878631,"spread":0.2719630142187733,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003932165,0.000695824,0.0003922704,0.00335724,0.0007563662,0.001326835,0.0002768737,0.0005359253,0.001460043],"category_scores_gemma":[0.000337256,0.000155535,0.0006583275,0.002271977,0.0004539034,0.0008278835,0.0004286072,0.0004194363,0.0006830996],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003203096,"about_ca_system_score_gemma":0.0004002475,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005217853,"about_ca_topic_score_gemma":0.008568678,"domain_scores_codex":[0.9996291,0.00003473866,0.00003915798,0.0001197845,0.00008177866,0.0000954182],"domain_scores_gemma":[0.9997717,0.00003925106,0.00005008494,0.00001161843,0.00008542703,0.00004193671],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001228628,0.0003409401,0.1864031,0.0002202788,0.0001806225,0.0003943047,0.0007609447,0.0005292883,0.7547284,0.0002666155,0.0002407431,0.05470612],"study_design_scores_gemma":[0.00001456026,0.0006647779,0.9125183,0.00009302914,0.0001903854,0.0005810458,0.002236932,0.002611644,0.07529609,0.0003956339,0.00535003,0.00004752388],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9926124,0.001061097,0.002037663,0.00005422182,0.00004571887,0.00006496753,0.001692839,0.00003138137,0.002399745],"genre_scores_gemma":[0.9866344,0.0007516379,0.008284095,0.00009243104,0.00002651944,0.00004832376,0.001836261,0.00002283931,0.002303477],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005217853,"threshold_uncertainty_score":0.01037496,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2080312475","doi":"10.1080/02773810009349624","title":"Differentiation of Jack Pine from Other Conifers by the Analysis of Color Appearance from Chemical Tests","year":2000,"lang":"en","type":"article","venue":"Journal of Wood Chemistry and Technology","topic":"Wood and Agarwood Research","field":"Chemistry","cited_by":3,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true},"ca_institutions":"Université du Québec à Trois-Rivières","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Chemistry; Pinus <genus>; Balsam; Pine wood; Botany; Horticulture","authors":[{"name":"Kwei Nam Law","is_ca":true},{"name":"B. V. Kokta","is_ca":true},{"name":"Changbin Mao","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.00538982661798237,"gpt":0.2290644872460516,"spread":0.2236746606280692,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001463421,0.0002974938,0.0001674061,0.0007240498,0.0003638918,0.000451176,0.0001133496,0.0001326137,0.0005683373],"category_scores_gemma":[0.0003552281,0.00009985753,0.00006975779,0.0002673676,0.0001433073,0.000168061,0.0001204576,0.0001515281,0.0002571628],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001559627,"about_ca_system_score_gemma":0.0002762274,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03139592,"about_ca_topic_score_gemma":0.07951013,"domain_scores_codex":[0.9999002,0.00001074848,0.000008052736,0.00002192705,0.00002538641,0.00003365552],"domain_scores_gemma":[0.9996277,0.00004574948,0.00006985237,0.00001315685,0.0001312876,0.0001122554],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0007501654,0.0001335458,0.2861973,0.0001092323,0.00002997027,0.000812281,0.0005201366,0.0001242092,0.6948847,0.0001166014,0.000107766,0.01621408],"study_design_scores_gemma":[0.000009406606,0.0003385193,0.9701675,0.00001442809,0.00002858684,0.0008688943,0.0006532627,0.0003244614,0.02597493,0.00005363494,0.00155623,0.00001022937],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9978375,0.0002323046,0.0004552811,0.000006691165,0.000003595448,0.00001573067,0.0001404921,0.00001689493,0.001291573],"genre_scores_gemma":[0.9962767,0.0001608429,0.001965676,0.00002920231,0.000004088241,0.00001057678,0.000499166,0.000007155671,0.001046631],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03139592,"threshold_uncertainty_score":0.06242633,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W6948275058","doi":"10.5061/dryad.1p55v","title":"Data from: Oxygen limitations on marine animal distributions and the collapse of epibenthic community structure during shoaling hypoxia","year":2015,"lang":"en","type":"dataset","venue":"Data Archiving and Networked Services (DANS)","topic":"Wood and Agarwood Research","field":"Chemistry","cited_by":3,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Victoria","funders":"","keywords":"Hypoxia (environmental); Benthic zone; Oxygen; Submarine pipeline; Shoaling and schooling; Copepod; Marine ecosystem; Community structure; Ecosystem; Marine life","authors":[],"retraction":null,"screen_n_in":null,"score":{"opus":0.06684393921898492,"gpt":0.2930726458296423,"spread":0.2262287066106574,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001986665,0.00009927306,0.0001281048,0.0005174961,0.0002164384,0.0002893559,0.0002296523,0.0002217779,0.003818843],"category_scores_gemma":[0.0008707063,0.00008459602,0.0001121454,0.0005695375,0.0001146717,0.0001648682,0.0003454154,0.0001973182,0.001002248],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002197526,"about_ca_system_score_gemma":0.0002297751,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02422856,"about_ca_topic_score_gemma":0.06671495,"domain_scores_codex":[0.9998527,0.00002102427,0.00001723212,0.00003076473,0.00005033407,0.00002795935],"domain_scores_gemma":[0.9991234,0.0001235707,0.0002854041,0.00007990905,0.0002283986,0.000159321],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003676328,0.00004353746,0.9819558,0.00006276741,0.00004117227,0.0000915974,0.0003150029,0.0002291872,0.004155242,0.00004980715,0.003960674,0.008727488],"study_design_scores_gemma":[0.000002495547,0.00001751419,0.9982862,0.00000405944,0.000004656253,0.00001111533,0.00007620583,0.00009715692,0.0001818637,0.000006937379,0.001310288,0.000001563084],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"dataset","genre_scores_codex":[0.9743935,0.0000463527,0.0002275345,0.00008468454,0.00001320976,0.00001833864,0.02244719,0.00002630304,0.002742893],"genre_scores_gemma":[0.9566224,0.00008393657,0.000582733,0.0000874959,0.00001265977,0.00006346894,0.03882611,0.00001880344,0.003702411],"genre_candidate":"dataset","genre_consensus":null,"teacher_disagreement_score":0.02422856,"threshold_uncertainty_score":0.0481751,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W6946509665","doi":"10.34649/at.2022.4.4.002","title":"Анализ датчиков автоматической системы обогрева стрелочных переводов","year":2022,"lang":"ru","type":"article","venue":"Russian Agency for Digital Standardization","topic":"Wood and Agarwood Research","field":"Chemistry","cited_by":3,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Royal Victoria Regional Health Centre","funders":"","keywords":"Process (computing); Identification (biology); Product (mathematics)","authors":[],"retraction":null,"screen_n_in":null,"score":{"opus":0.01617860136173514,"gpt":0.2706345939881054,"spread":0.2544559926263702,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00125508,0.0005196861,0.0003870912,0.001903509,0.002478292,0.006084275,0.0007206279,0.001462615,0.03417214],"category_scores_gemma":[0.00401991,0.0006584298,0.0005542559,0.001497344,0.004187723,0.004123424,0.002052934,0.002182414,0.009175143],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002138779,"about_ca_system_score_gemma":0.003134284,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002576582,"about_ca_topic_score_gemma":0.002844075,"domain_scores_codex":[0.997604,0.0004710008,0.0001127343,0.0004603837,0.001084917,0.0002669765],"domain_scores_gemma":[0.9981184,0.0005344848,0.0001800106,0.0003617793,0.0006388337,0.0001665388],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00006467953,0.00004577517,0.0008158925,0.000251521,0.0000234673,0.000367613,0.002028902,0.001084882,0.01177193,0.9044756,0.006729579,0.07234017],"study_design_scores_gemma":[0.00004059707,0.00007026832,0.002927915,0.0002340616,0.00004709303,0.0007843384,0.002386343,0.00224523,0.0160296,0.4228711,0.5522646,0.00009893246],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.04654697,0.008801744,0.1421226,0.006838442,0.001553376,0.0001900096,0.0006296111,0.0004908263,0.7928264],"genre_scores_gemma":[0.6890033,0.008870142,0.1131697,0.0009132359,0.0006389895,0.0006021431,0.000503576,0.0006251197,0.1856737],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03417214,"threshold_uncertainty_score":0.1143172,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W6948308512","doi":"10.5061/dryad.7s848","title":"Data from: Landscape genomics of Populus trichocarpa: the role of hybridization, limited gene flow and natural selection in shaping patterns of population structure","year":2014,"lang":"en","type":"dataset","venue":"Data Archiving and Networked Services (DANS)","topic":"Wood and Agarwood Research","field":"Chemistry","cited_by":2,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of British Columbia","funders":"","keywords":"Gene flow; Introgression; Populus trichocarpa; Population genomics; Natural selection; Population; Ecotype; Allele frequency","authors":[],"retraction":null,"screen_n_in":null,"score":{"opus":0.01525815044919156,"gpt":0.24586309872836,"spread":0.2306049482791684,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008392872,0.001187159,0.0009043808,0.001863671,0.0006673851,0.00109782,0.001717287,0.0008835534,0.0135908],"category_scores_gemma":[0.002344557,0.0005000028,0.0008154907,0.003218963,0.0003631562,0.0005849182,0.001248544,0.001156351,0.01038117],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009576032,"about_ca_system_score_gemma":0.002167496,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03055868,"about_ca_topic_score_gemma":0.06093991,"domain_scores_codex":[0.9994661,0.00006483151,0.00006075436,0.0001559299,0.0001619849,0.00009034383],"domain_scores_gemma":[0.9990594,0.0001771708,0.0001622045,0.0001963561,0.000254583,0.000150301],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0007756388,0.0002453381,0.02851174,0.003853092,0.0005305933,0.0002853878,0.0004394035,0.002808592,0.0118989,0.001977753,0.9319795,0.0166941],"study_design_scores_gemma":[0.00116374,0.00007184784,0.1600879,0.0002330649,0.0001861525,0.0001730528,0.0002228347,0.001516522,0.004666836,0.001405335,0.8301869,0.00008576056],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.003550944,0.00007756388,0.0001653858,0.00006262503,0.0000124484,0.00002221418,0.9950905,0.0004101015,0.0006082493],"genre_scores_gemma":[0.002888972,0.00004497548,0.0006296716,0.00001952252,0.000003198384,0.00006947654,0.9959026,0.00006396494,0.0003775935],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.03055868,"threshold_uncertainty_score":0.06076163,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W6948856866","doi":"10.5061/dryad.qn1cj","title":"Data from: Temporally dynamic habitat suitability predicts genetic relatedness among caribou","year":2014,"lang":"en","type":"dataset","venue":"Data Archiving and Networked Services (DANS)","topic":"Wood and Agarwood Research","field":"Chemistry","cited_by":2,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"Ministère des Ressources naturelles et des Forêts; Center for Northern Studies; Université Laval","funders":"","keywords":"Habitat; Selection (genetic algorithm); Vegetation (pathology); Landscape connectivity; Climate change; Genetic structure; Spatial heterogeneity; Temporal scales","authors":[],"retraction":null,"screen_n_in":null,"score":{"opus":0.02249198426294621,"gpt":0.2731899547601104,"spread":0.2506979704971642,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007493889,0.001266236,0.0008902831,0.002121193,0.000771226,0.00134298,0.002416365,0.001188784,0.01130772],"category_scores_gemma":[0.004462737,0.0004440619,0.001033841,0.003976751,0.0003767975,0.0005649484,0.001155283,0.001109965,0.009705653],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003796127,"about_ca_system_score_gemma":0.005132056,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.6098154,"about_ca_topic_score_gemma":0.7650884,"domain_scores_codex":[0.9995295,0.00006399391,0.00004388135,0.0001362337,0.0001222725,0.0001042213],"domain_scores_gemma":[0.9984285,0.0002759211,0.0001715401,0.0002711841,0.0006730717,0.0001797435],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.0002657811,0.0001097378,0.05256942,0.001291848,0.0002994813,0.0001454311,0.0002403675,0.003653582,0.000565672,0.001040544,0.9295495,0.01026866],"study_design_scores_gemma":[0.0006329732,0.00004030071,0.221864,0.0004764123,0.0001543117,0.0001493699,0.0004279765,0.007146792,0.00110159,0.001697371,0.7661823,0.0001266056],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.002797136,0.00009339205,0.0001113634,0.00008737583,0.00001132692,0.00001462946,0.9961958,0.0002448325,0.0004440979],"genre_scores_gemma":[0.005124558,0.00006937527,0.0005683569,0.00002693325,0.0000039416,0.00006695849,0.9934368,0.00003665714,0.0006664534],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.6098154,"threshold_uncertainty_score":0.784965,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W6948386232","doi":"10.5061/dryad.qb87r","title":"Data from: Spatial patterns of immunogenetic and neutral variation underscore the conservation value of small, isolated American badger populations","year":2016,"lang":"en","type":"dataset","venue":"Data Archiving and Networked Services (DANS)","topic":"Wood and Agarwood Research","field":"Chemistry","cited_by":2,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Ministry of Natural Resources and Forestry; University of Guelph; Trent University","funders":"","keywords":"Subspecies; Gene flow; Genetic diversity; Local adaptation; Genetic variation; Adaptive value; Genetic drift; Badger; Spatial ecology","authors":[],"retraction":null,"screen_n_in":null,"score":{"opus":0.04875465280255215,"gpt":0.2870197747847469,"spread":0.2382651219821947,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001232986,0.001158719,0.001119501,0.00311818,0.0006496044,0.00161666,0.001638122,0.0009431533,0.02997027],"category_scores_gemma":[0.00514573,0.0005026473,0.0006636723,0.00663848,0.0004430955,0.001042663,0.001717967,0.001401245,0.02768329],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00115671,"about_ca_system_score_gemma":0.002403406,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02831939,"about_ca_topic_score_gemma":0.05179098,"domain_scores_codex":[0.9990178,0.0001140902,0.000147601,0.0002654385,0.0003073314,0.0001476486],"domain_scores_gemma":[0.9980391,0.0005388333,0.000341166,0.0004416546,0.0004559067,0.0001833117],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002741066,0.00006572167,0.01520224,0.002334058,0.0001511795,0.0001058228,0.0001913946,0.001139515,0.001220331,0.001635538,0.9663254,0.01135481],"study_design_scores_gemma":[0.0002978965,0.00001651744,0.04481168,0.000263891,0.00004889067,0.00007285078,0.0001653993,0.0004861986,0.0009275767,0.001234372,0.9516389,0.00003572933],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.000955462,0.00006585216,0.00009283226,0.00006931635,0.00001372556,0.000009890761,0.997754,0.0002485481,0.0007904924],"genre_scores_gemma":[0.001591725,0.00006453902,0.0003762111,0.00002016414,0.000003974494,0.0000562702,0.9972882,0.00006866227,0.0005303755],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.02997027,"threshold_uncertainty_score":0.1002605,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4407930119","doi":"10.1007/s00226-025-01636-8","title":"Unsupervised wood species identification based on multiobjective optimal clustering and feature fusion","year":2025,"lang":"en","type":"article","venue":"Wood Science and Technology","topic":"Wood and Agarwood Research","field":"Chemistry","cited_by":2,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of British Columbia","funders":"","keywords":"Identification (biology); Cluster analysis; Feature (linguistics); Fusion; Artificial intelligence; Pattern recognition (psychology); Computer science; Engineering; Mathematics; Biology; Botany","authors":[{"name":"Yuan Wang","is_ca":false},{"name":"Wen-Jin Ma","is_ca":false},{"name":"Ren-He Qu","is_ca":false},{"name":"Stavros Avramidis","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.009943913753053705,"gpt":0.2644120739454686,"spread":0.2544681601924149,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008620963,0.0009083083,0.001314998,0.00232257,0.0007426441,0.0009601635,0.000949265,0.000913304,0.000905657],"category_scores_gemma":[0.001294204,0.0004687832,0.001599544,0.001635806,0.0004854299,0.001157356,0.0009576196,0.0005599342,0.0003868522],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004915457,"about_ca_system_score_gemma":0.0008235709,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003048996,"about_ca_topic_score_gemma":0.003821819,"domain_scores_codex":[0.9994228,0.00009779744,0.00003739494,0.0001728383,0.0001820657,0.00008715689],"domain_scores_gemma":[0.9993962,0.0001885084,0.00008484499,0.00007110215,0.000224349,0.00003501525],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0003761523,0.000360855,0.004510127,0.0002049266,0.0002860507,0.0001274762,0.0002557714,0.3776107,0.09244861,0.004098927,0.001725445,0.5179949],"study_design_scores_gemma":[0.000005734687,0.00003839892,0.001742628,0.000005803249,0.00002601955,0.00003115861,0.00003713798,0.9901536,0.005539906,0.002130597,0.0002704615,0.00001854067],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05565107,0.0001527765,0.9425008,0.00005020571,0.00002183643,0.00006106769,0.0001136563,0.000430816,0.001017689],"genre_scores_gemma":[0.5222579,0.0001111124,0.4754395,0.00003991483,0.00002845723,0.0001317965,0.0005272957,0.0001090565,0.00135489],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003048996,"threshold_uncertainty_score":0.006062508,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4319458806","doi":"10.18671/scifor.v51.12","title":"Heartwood-Sapwood-Bark profiles and association studies in Pterocarpus marsupium Roxb., a vulnerable antidiabetic forestry species of sub- tropical forest","year":2023,"lang":"en","type":"article","venue":"Scientia Forestalis","topic":"Wood and Agarwood Research","field":"Chemistry","cited_by":1,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false},"ca_institutions":"","funders":"Indian Council of Forestry Research and Education; Terry Fox Research Institute","keywords":"Bark (sound); Forestry; Tropical forest; Botany; Biology; Geography; Ecology","authors":[{"name":"Naseer Mohammad","is_ca":false},{"name":"Sengodan Saravanan","is_ca":false},{"name":"Fatima Shirin","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.03436770171908543,"gpt":0.294994780251413,"spread":0.2606270785323275,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000160142,0.0001952295,0.0001449724,0.000965444,0.0003537637,0.0002750514,0.0001883391,0.0001579811,0.0007255677],"category_scores_gemma":[0.0002605777,0.0001150053,0.0001553505,0.0006237363,0.0001761581,0.0001563588,0.0002311245,0.0001704208,0.0001130322],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007341856,"about_ca_system_score_gemma":0.00005063878,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001455104,"about_ca_topic_score_gemma":0.003562968,"domain_scores_codex":[0.9998974,0.00002288118,0.000009519667,0.0000409994,0.0000127791,0.00001649189],"domain_scores_gemma":[0.9997475,0.00003101423,0.0001278821,0.00002354336,0.00002423349,0.00004592431],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001417149,0.00007619702,0.9695811,0.00003359392,0.00006028262,0.0005758726,0.001110973,0.00006891691,0.02072988,0.0000273965,0.00005463143,0.007539371],"study_design_scores_gemma":[5.53302e-7,0.00004583099,0.9990041,0.000001347919,0.000007608676,0.0003396613,0.0002638677,0.00005875524,0.000192008,0.000007805857,0.00007692622,0.000001541487],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9997926,0.00006013105,0.00004105422,0.00000266366,5.204022e-7,0.000001590936,0.00003839028,9.568596e-7,0.00006208254],"genre_scores_gemma":[0.9996056,0.00003498967,0.0001851767,0.000003421264,0.000001375837,0.000003243181,0.00005971553,5.883167e-7,0.0001059559],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001455104,"threshold_uncertainty_score":0.002893329,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W6948035955","doi":"10.48336/azar-yx75","title":"Coupling of multi-agent based simulation and particle swarm optimization for environmental planning and decision making","year":2022,"lang":"en","type":"article","venue":"Memorial University Research Repository (Memorial University)","topic":"Wood and Agarwood Research","field":"Chemistry","cited_by":1,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Particle swarm optimization; Convergence (economics); Multi-swarm optimization; Process (computing); Computation; Coupling (piping); Swarm behaviour","authors":[],"retraction":null,"screen_n_in":null,"score":{"opus":0.04703380939033613,"gpt":0.2941902735790277,"spread":0.2471564641886916,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001044221,0.0006827117,0.0006374457,0.0006066773,0.0004247872,0.001161561,0.0008287217,0.000868669,0.0009972203],"category_scores_gemma":[0.001921113,0.0004674993,0.0008125821,0.0006198939,0.0005669573,0.0009635978,0.001110482,0.0009978618,0.0001790268],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006440697,"about_ca_system_score_gemma":0.001240519,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005467641,"about_ca_topic_score_gemma":0.004287152,"domain_scores_codex":[0.9992083,0.0003626857,0.00004823521,0.00008708925,0.0002519566,0.00004184087],"domain_scores_gemma":[0.9993066,0.0004169765,0.00007080259,0.00006410674,0.0001130097,0.00002853754],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001726546,0.00003183318,0.0005612587,0.0000540307,0.00004411283,0.0000516371,0.00004486972,0.9698362,0.001415187,0.008768247,0.0001719996,0.01900337],"study_design_scores_gemma":[0.000003596934,0.00001484257,0.00008202464,0.000004498548,0.000006293238,0.000007251386,0.000007535016,0.9970027,0.000327697,0.001811786,0.0007277532,0.00000406821],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01213683,0.000236163,0.9826667,0.0001331352,0.00005488356,0.00006960976,0.00001393502,0.0001432113,0.00454562],"genre_scores_gemma":[0.7272459,0.0008823469,0.2681796,0.0000945076,0.00005990118,0.0003295172,0.00008305462,0.00005351624,0.003071666],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005467641,"threshold_uncertainty_score":0.01087165,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4387462707","doi":"10.14710/jil.21.4.987-991","title":"Kajian Inventarisasi Keanekaragaman Jenis Flora dan Fauna Hutan Lindung Kasinan Kota Batu","year":2023,"lang":"id","type":"article","venue":"Jurnal Ilmu Lingkungan","topic":"Wood and Agarwood Research","field":"Chemistry","cited_by":1,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Encana (Canada)","funders":"","keywords":"Forestry; Biology; Geography","authors":[{"name":"Mohammad Sulthon Neagara","is_ca":false},{"name":"Fuad Muhammad","is_ca":false},{"name":"Maryono Maryono","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.03545288717723109,"gpt":0.2969195253890643,"spread":0.2614666382118332,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002964329,0.0002365897,0.0002324028,0.0009735345,0.001199565,0.001340228,0.0002454876,0.0002335107,0.01019975],"category_scores_gemma":[0.0003081312,0.0001779797,0.0002229674,0.00165773,0.000455429,0.0007552109,0.0007410009,0.0003310826,0.001148109],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001357976,"about_ca_system_score_gemma":0.001913605,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03720992,"about_ca_topic_score_gemma":0.2356584,"domain_scores_codex":[0.9997633,0.00002267306,0.00001234884,0.00007536596,0.00007377136,0.00005254192],"domain_scores_gemma":[0.9997345,0.00004747227,0.00004263796,0.00002037441,0.00009975837,0.00005526936],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002281433,0.0002025999,0.680508,0.0010384,0.0001941062,0.0008422089,0.01542563,0.0004990008,0.03279506,0.004844652,0.003148136,0.2602741],"study_design_scores_gemma":[0.000003326234,0.0001098906,0.9351152,0.0001594862,0.0001135257,0.0003108287,0.01408466,0.0001293401,0.003847177,0.0004104593,0.04569655,0.00001944672],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9283059,0.003352706,0.0009053744,0.0003155988,0.00003257596,0.00004354393,0.001257237,0.00004543892,0.06574173],"genre_scores_gemma":[0.929893,0.004250909,0.002806385,0.0001125841,0.00001580149,0.00005012742,0.001204756,0.00002808227,0.06163829],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03720992,"threshold_uncertainty_score":0.07398671,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4409333171","doi":"10.3390/f16040645","title":"Cork Oak Regeneration Prediction Through Multilayer Perceptron Architectures","year":2025,"lang":"en","type":"article","venue":"Forests","topic":"Wood and Agarwood Research","field":"Chemistry","cited_by":1,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Université du Québec à Chicoutimi","funders":"European Regional Development Fund; Fundação para a Ciência e a Tecnologia; Interreg; Universidade de Trás-os-Montes e Alto Douro","keywords":"Cork; Regeneration (biology); Quercus suber; Natural regeneration; Java; Fagaceae; Environmental science; Forestry; Computer science; Geography; Ecology; Biology; Botany; Programming language","authors":[{"name":"Angelo Fierravanti","is_ca":false},{"name":"Lorena Balducci","is_ca":true},{"name":"Teresa Fonseca","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.01447746340283152,"gpt":0.2906238660367074,"spread":0.2761464026338759,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001539365,0.0009145684,0.0004050211,0.0006979546,0.000216149,0.0007726199,0.0005236776,0.0005076728,0.0005523968],"category_scores_gemma":[0.001666866,0.0002732721,0.000610325,0.0004572629,0.0002032304,0.0006756693,0.0004270587,0.0006771148,0.0002421566],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007306217,"about_ca_system_score_gemma":0.0005027805,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009952771,"about_ca_topic_score_gemma":0.007930941,"domain_scores_codex":[0.9997272,0.00007983573,0.00001881047,0.0000719237,0.00004919545,0.00005299443],"domain_scores_gemma":[0.9994217,0.0003064366,0.00006765378,0.00003315644,0.0001407583,0.00003036012],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002302932,0.0001786762,0.009792584,0.00006237716,0.0001045031,0.00009995315,0.00005540907,0.873858,0.004389818,0.0006428849,0.0006298152,0.1099557],"study_design_scores_gemma":[0.000001579848,0.00002456773,0.000797206,0.000003476529,0.000005335741,0.000004297066,0.00000473478,0.998423,0.0004021612,0.0002723302,0.00005812241,0.000003167657],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.7051101,0.001400032,0.2872803,0.0004088471,0.0001254855,0.00007221127,0.0002862421,0.001494161,0.003822719],"genre_scores_gemma":[0.9827834,0.0001893566,0.01565055,0.00003508582,0.00001641863,0.00001750246,0.0001368243,0.000009122201,0.001161698],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.009952771,"threshold_uncertainty_score":0.0197897,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4410897740","doi":"10.1186/s10086-025-02199-9","title":"Dynamic visualisation of a solvent-borne preservative in wood using confocal laser scanning microscopy","year":2025,"lang":"en","type":"article","venue":"Journal of Wood Science","topic":"Wood and Agarwood Research","field":"Chemistry","cited_by":1,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of British Columbia","funders":"Japan Society for the Promotion of Science","keywords":"Preservative; Confocal laser scanning microscopy; Materials science; Confocal; Confocal microscopy; Microscopy; Solvent; Laser; Confocal laser scanning microscope; Laser scanning; Visualization; Analytical Chemistry (journal); Composite material; Optics; Chromatography; Chemistry; Biomedical engineering; Organic chemistry; Engineering; Mechanical engineering","authors":[{"name":"Hiroki Sakagami","is_ca":false},{"name":"Yuchi Zhang","is_ca":false},{"name":"Teruhisa Miyauchi","is_ca":false},{"name":"Philip D. Evans","is_ca":true},{"name":"Hiroshi Matsunaga","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.02811605386239473,"gpt":0.3791568335747921,"spread":0.3510407797123974,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002837037,0.0002359807,0.0001566872,0.0003701356,0.0002047785,0.0002230114,0.000268722,0.0002878247,0.0009339311],"category_scores_gemma":[0.0001502565,0.0001375279,0.0001372523,0.0001746474,0.000262659,0.0003442228,0.000205755,0.0004190654,0.0002164836],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002913348,"about_ca_system_score_gemma":0.0002874084,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001513368,"about_ca_topic_score_gemma":0.002045701,"domain_scores_codex":[0.9999045,0.00001286044,0.000006029671,0.00002378925,0.00002899831,0.00002374831],"domain_scores_gemma":[0.9998111,0.0000632002,0.00003610337,0.00001860829,0.00005362596,0.0000173373],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000007247952,0.00000310395,0.00008727542,0.00001397639,6.641698e-7,0.00001824708,0.00001221694,0.00004974805,0.9991208,0.0000366387,0.00001269113,0.0006373787],"study_design_scores_gemma":[0.000002581653,0.00008515782,0.00300986,0.00000569922,0.000003771793,0.0001413597,0.00004990064,0.002752681,0.9928341,0.00003899103,0.001067969,0.000007912493],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9492956,0.001169105,0.04704233,0.00008421551,0.00002042876,0.00005098682,0.0002304616,0.0002076216,0.001899289],"genre_scores_gemma":[0.9323992,0.0009163223,0.06398512,0.00006656961,0.00001308408,0.00007037257,0.00020291,0.00004877588,0.002297638],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001513368,"threshold_uncertainty_score":0.003124356,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W6948412050","doi":"10.5061/dryad.1bt27","title":"Data from: Always chew your food: freshwater stingrays use mastication to process tough insect prey","year":2016,"lang":"en","type":"dataset","venue":"Data Archiving and Networked Services (DANS)","topic":"Wood and Agarwood Research","field":"Chemistry","cited_by":1,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Toronto","funders":"","keywords":"Predation; Mastication; Insect; Crypsis; Generalist and specialist species","authors":[],"retraction":null,"screen_n_in":null,"score":{"opus":0.1045986522412834,"gpt":0.3167406556404881,"spread":0.2121420033992047,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001240965,0.0006787285,0.0006124837,0.001844513,0.0007087087,0.002540448,0.001090943,0.001259295,0.252469],"category_scores_gemma":[0.009997115,0.0004302904,0.0004140344,0.001952415,0.0004752054,0.00215611,0.00228436,0.0008571845,0.1601804],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006933315,"about_ca_system_score_gemma":0.001595526,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006167314,"about_ca_topic_score_gemma":0.008951697,"domain_scores_codex":[0.9991086,0.00008114881,0.0001737536,0.0002034125,0.000366301,0.00006679112],"domain_scores_gemma":[0.9945865,0.001024002,0.000544714,0.00151715,0.001868198,0.0004595093],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0008088165,0.0001220677,0.01673106,0.002223948,0.00005561187,0.0003554687,0.0005430575,0.0004471866,0.008466218,0.00125274,0.814727,0.1542668],"study_design_scores_gemma":[0.0001230944,0.0001013783,0.07203782,0.0008635394,0.00006834319,0.0004343431,0.0004809517,0.003753691,0.009886465,0.001991043,0.9101028,0.0001565058],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.01705533,0.0004250008,0.009333095,0.003498759,0.001378328,0.0007729324,0.7664244,0.03518934,0.1659229],"genre_scores_gemma":[0.1367146,0.00135422,0.02353646,0.001819172,0.0004383375,0.001364419,0.6893644,0.008200899,0.1372076],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.252469,"threshold_uncertainty_score":0.8445929,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W4407987101","doi":"10.18280/isi.300214","title":"Learning Model Based on Artificial Intelligence to Determine Wood Quality: A Systematic Review","year":2025,"lang":"en","type":"review","venue":"Ingénierie des systèmes d information","topic":"Wood and Agarwood Research","field":"Chemistry","cited_by":1,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false},"ca_institutions":"","funders":"","keywords":"Quality (philosophy); Artificial intelligence; Computer science; Machine learning; Epistemology","authors":[{"name":"Dino Quinteros-Navarro","is_ca":false},{"name":"Alfredo Quinteros","is_ca":false},{"name":"Victor Muñoz","is_ca":false},{"name":"W. Fred Ramirez","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.07729894026254172,"gpt":0.3573013429801895,"spread":0.2800024027176478,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008052137,0.001771242,0.008358967,0.00538092,0.0003520288,0.002263666,0.002432889,0.001556457,0.003504652],"category_scores_gemma":[0.02642132,0.0007586483,0.008532088,0.00484753,0.000831365,0.002337512,0.0009720974,0.001414167,0.0002980789],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001704513,"about_ca_system_score_gemma":0.005642275,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007627318,"about_ca_topic_score_gemma":0.01794153,"domain_scores_codex":[0.9959223,0.001662519,0.001071451,0.0004358283,0.0008328788,0.00007499548],"domain_scores_gemma":[0.9819912,0.01516942,0.001605834,0.0002850445,0.0008437216,0.000104801],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"systematic_review","study_design_gemma":"systematic_review","study_design_scores_codex":[0.0006850844,0.0002212539,0.003217613,0.677688,0.03880295,0.0001239049,0.0001660385,0.002210395,0.0002302653,0.0009891164,0.002433089,0.2732323],"study_design_scores_gemma":[0.002176029,0.00191052,0.01394417,0.4911845,0.4416741,0.000677734,0.0005190743,0.005398707,0.0007800856,0.004273911,0.03720857,0.0002526449],"study_design_candidate":"systematic_review","study_design_consensus":"systematic_review","genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.001719378,0.9959379,0.001223634,0.000269578,0.000070817,0.0002875719,0.0002236291,0.00001679104,0.0002506886],"genre_scores_gemma":[0.03177239,0.962515,0.004415163,0.000466404,0.00006998919,0.0003596715,0.0002388815,0.000007685303,0.0001547675],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.008358967,"threshold_uncertainty_score":0.0425843,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W6944732929","doi":"10.20381/ruor-28624","title":"Testing of the Thermo-Hydro-Mechanical-Chemical (THMC) Behavior of Lime-Treated Subgrade Marine Clays Subjected to Environmental Stresses","year":2022,"lang":"en","type":"article","venue":"uO Research (University of Ottawa)","topic":"Wood and Agarwood Research","field":"Chemistry","cited_by":1,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"","keywords":"Subgrade; Lime; Foundation (evidence); Soil stabilization; Pore water pressure; Earthworks; Asphalt","authors":[],"retraction":null,"screen_n_in":null,"score":{"opus":0.03806141333423531,"gpt":0.2595139243568246,"spread":0.2214525110225893,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002701356,0.0002188948,0.0002622881,0.0001818417,0.0002708451,0.0002558441,0.0002657039,0.0002910924,0.001207817],"category_scores_gemma":[0.0003546741,0.0001232372,0.0002280681,0.000201663,0.0002442761,0.0001788026,0.0001524819,0.0003781269,0.000196803],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003213416,"about_ca_system_score_gemma":0.0002916071,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008544989,"about_ca_topic_score_gemma":0.01892042,"domain_scores_codex":[0.999805,0.00001704316,0.00001596208,0.00003763246,0.00007218472,0.00005212874],"domain_scores_gemma":[0.999577,0.00008837216,0.00007951746,0.00003692429,0.000148905,0.00006929124],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000300196,0.0001091131,0.002558594,0.00006102145,0.00001044765,0.00004977283,0.00009984423,0.000437513,0.9944324,0.00001936706,0.00002729712,0.001894408],"study_design_scores_gemma":[0.000006265985,0.001411483,0.01951219,0.00000623992,0.00001806433,0.00002347002,0.000145887,0.001492604,0.9769912,0.00001046422,0.0003744027,0.000007707477],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9990688,0.00007714551,0.0003060653,0.000008135514,0.000005827023,0.00001565923,0.0001701159,0.00001033863,0.0003380415],"genre_scores_gemma":[0.997902,0.0001448822,0.0006072652,0.00001373027,0.000002582037,0.00001868775,0.0001283413,0.000004830747,0.001177569],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008544989,"threshold_uncertainty_score":0.01699048,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W6947591113","doi":"10.4231/d3t14tq2r","title":"Numerical Simulation of the Seismic Response of Steel X-Braced Frames with Single Shear Bolted Connections","year":2014,"lang":"en","type":"article","venue":"PolyPublie (École Polytechnique de Montréal)","topic":"Wood and Agarwood Research","field":"Chemistry","cited_by":1,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"","keywords":"OpenSees; Bracing; Brace; Dissipation; Connection (principal bundle); Seismic retrofit; Seismic analysis; Buckling; Shear wall; Computer simulation","authors":[],"retraction":null,"screen_n_in":null,"score":{"opus":0.01146830989172256,"gpt":0.2425392766188448,"spread":0.2310709667271222,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000291139,0.0004780921,0.000484589,0.0003952149,0.0004410353,0.0005417469,0.0007658241,0.001230255,0.002007989],"category_scores_gemma":[0.0008622138,0.0003065139,0.0005008772,0.0004364892,0.0006447008,0.0003215175,0.0004470905,0.000453914,0.0002281061],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006783075,"about_ca_system_score_gemma":0.0008216998,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01524879,"about_ca_topic_score_gemma":0.009067591,"domain_scores_codex":[0.9998782,0.00002510625,0.000007503591,0.0000185757,0.00003952722,0.00003107152],"domain_scores_gemma":[0.9997008,0.0001423496,0.00004987396,0.00001943442,0.0000568116,0.00003085498],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002356658,0.00002015737,0.0008996408,0.00001432562,0.000006619397,0.00006311147,0.00002842915,0.9957353,0.001835992,0.0004166581,0.00005995183,0.0008962697],"study_design_scores_gemma":[0.00000360281,0.0000137508,0.0002210158,0.00000177841,0.000001465913,0.000004823448,0.00001127856,0.9993098,0.0003152269,0.00005015413,0.00006478682,0.000002293172],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9208803,0.0001632102,0.06109316,0.000177233,0.00006638153,0.0001064381,0.0005000752,0.00040711,0.01660615],"genre_scores_gemma":[0.9873695,0.00009412643,0.009714412,0.0000237638,0.000006213281,0.00006788815,0.0001891068,0.0000234995,0.002511568],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01524879,"threshold_uncertainty_score":0.03032011,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W6947892369","doi":"10.48550/arxiv.astro-ph/0210043","title":"The Wide-Field Imaging Interferometry Testbed III. Metrology Subsystem","year":2002,"lang":"en","type":"preprint","venue":"CERN Document Server (European Organization for Nuclear Research)","topic":"Wood and Agarwood Research","field":"Chemistry","cited_by":1,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Natural Sciences and Engineering Research Council of Canada","funders":"","keywords":"Testbed; Metrology; Interferometry; Detector; Astronomical interferometer; Displacement (psychology)","authors":[],"retraction":null,"screen_n_in":null,"score":{"opus":0.02769252298850852,"gpt":0.2753784661318393,"spread":0.2476859431433308,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001521784,0.0008210372,0.0004505249,0.0005949396,0.0006321465,0.000777506,0.001034126,0.0005782058,0.007585284],"category_scores_gemma":[0.0005224008,0.0002805545,0.0001876337,0.0007680485,0.0004143775,0.0008251435,0.0007133652,0.0006478821,0.003186475],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009010324,"about_ca_system_score_gemma":0.0008145017,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001514401,"about_ca_topic_score_gemma":0.00150687,"domain_scores_codex":[0.999433,0.0001214324,0.0000219871,0.00009181585,0.0002258651,0.0001057737],"domain_scores_gemma":[0.9996951,0.00002105659,0.00002934345,0.0001030838,0.00005996068,0.0000915772],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.002677771,0.0008348679,0.005915641,0.0004633252,0.00005810444,0.0006662098,0.0002706478,0.03090534,0.709213,0.06663296,0.05755347,0.1248087],"study_design_scores_gemma":[0.0008216574,0.00175882,0.01366199,0.0000645309,0.00002784677,0.000899008,0.0001590088,0.1325655,0.5191741,0.01145927,0.3193082,0.0001001314],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4115717,0.001821787,0.4011954,0.00180501,0.0005106422,0.002563151,0.03134797,0.04051857,0.1086658],"genre_scores_gemma":[0.5886396,0.0005664709,0.342645,0.0002532107,0.0001285438,0.001289595,0.03871104,0.002124321,0.02564211],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007585284,"threshold_uncertainty_score":0.02537531,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W6948873623","doi":"10.5255/ukda-sn-6888-20","title":"Small- and Medium-Sized Enterprise Finance Monitor, 2011-2017","year":2018,"lang":"en","type":"dataset","venue":"UK Data Archive","topic":"Wood and Agarwood Research","field":"Chemistry","cited_by":1,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"","keywords":"Demographics; Quarter (Canadian coin); Sample (material); Survey data collection; Telephone survey; Business risks; Small business","authors":[],"retraction":null,"screen_n_in":null,"score":{"opus":0.04283553709367522,"gpt":0.3020734171857591,"spread":0.2592378800920839,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004800335,0.0004752734,0.0003539967,0.003179769,0.0006586183,0.002408251,0.0007180482,0.0006809423,0.01204918],"category_scores_gemma":[0.01566193,0.0003599359,0.0002575841,0.005362093,0.0002984364,0.002006013,0.001932696,0.001004897,0.01143313],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004805201,"about_ca_system_score_gemma":0.01041041,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1001843,"about_ca_topic_score_gemma":0.130768,"domain_scores_codex":[0.9961843,0.0002713804,0.0003842198,0.0002597405,0.002277072,0.0006233182],"domain_scores_gemma":[0.9825988,0.001161262,0.002387888,0.000629091,0.01090279,0.002320153],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003077787,0.00007453232,0.05644309,0.0003844083,0.00001605104,0.00006147683,0.0003169909,0.0001451246,0.0002826265,0.001762846,0.8933975,0.04680774],"study_design_scores_gemma":[0.00003200776,0.00007972398,0.3072556,0.000222769,0.000009844282,0.00004755626,0.000675634,0.0002475925,0.0005879226,0.0001904276,0.6906284,0.00002256221],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.07530528,0.003632614,0.00163559,0.01549063,0.002831937,0.000875989,0.7952632,0.001327952,0.1036367],"genre_scores_gemma":[0.1378659,0.005591945,0.003433031,0.003825326,0.001053087,0.002730624,0.6471761,0.0004571454,0.1978669],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1001843,"threshold_uncertainty_score":0.1992024,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null}]}