{"meta":{"query_hash":"92444118e4eb","filters":{"venue":"Archives of Mining Sciences"},"cohort_total":9,"direct_labels_cover":0,"predictions_cover":9,"exported":9,"export_cap":100000,"truncated":false,"label_status":"direct model label, unvalidated","prediction_status":"machine_predicted_unvalidated (Codex and Gemma teacher distillation)","score_status":"score_only:v0-immature-baseline","snapshot":{"source":"OpenAlex, pinned release, all 482 partitions","release":"2026-06-24","frame_built":"2026-07-12"},"permalink":"https://metacan.xera.ac/q/92444118e4eb","api":"https://metacan.xera.ac/api/v1/cohort?venue=Archives+of+Mining+Sciences"},"results":[{"id":"W1993202616","doi":"10.2478/amsc-2013-0003","title":"Integration of Stream Sediment Geochemical and Aster Data for Porphyry Copper Deposit Exploration in Khatun Abad, North West of Iran / Integracja geochemicznych danych o osadach dennych oraz danych pozyskanych z systemu aster do poszukiwań geologicznych w rejonie złóż miedzi porfirytowej w khatun abad, w północno-zachodniej części iranu","year":2013,"lang":"en","type":"article","venue":"Archives of Mining Sciences","topic":"Geochemistry and Geologic Mapping","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"ASTER","funders":"","keywords":"Advanced Spaceborne Thermal Emission and Reflection Radiometer; Porphyry copper deposit; Alunite; Geology; Hydrothermal circulation; Geochemistry; Mineral exploration; Sediment; Mineralization (soil science); Mining engineering; Mineralogy; Remote sensing; Geomorphology; Digital elevation model; Soil science","score_opus":0.05431702680933392,"score_gpt":0.27128731721481825,"score_spread":0.21697029040548432,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1993202616","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9775873,0.0007205495,0.015186451,0.001338705,0.0002742131,0.0011401518,0.00010217561,0.000056848046,0.0035936106],"genre_scores_gemma":[0.924032,0.00009136997,0.07511737,0.00008331959,0.00007372447,0.0001243278,0.00025849204,0.000014050611,0.00020538978],"study_design_codex":"observational","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9944273,0.00027925693,0.0017568591,0.0017629765,0.0008838704,0.00088971143],"domain_scores_gemma":[0.9952301,0.0013349318,0.0012104413,0.0015953749,0.0003969357,0.00023223886],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0016218937,0.0006092145,0.0010181817,0.00056471454,0.0002624159,0.00025586036,0.003141765,0.00025446754,0.000031502947],"category_scores_gemma":[0.0007808636,0.00050508865,0.00017327411,0.0010037986,0.0012800038,0.0022023907,0.0013505971,0.0004215779,0.0000041855506],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00044923465,0.0014646385,0.46550056,0.0017695442,0.0002448664,0.000022739447,0.026376758,0.0009334504,0.4427845,0.002768533,0.0012997875,0.056385405],"study_design_scores_gemma":[0.0070622195,0.004494027,0.31043878,0.0064682467,0.0003042078,0.00047459066,0.04198475,0.21542771,0.3964889,0.012916924,0.0006634926,0.0032761628],"about_ca_topic_score_codex":0.00081368355,"about_ca_topic_score_gemma":0.0005190288,"teacher_disagreement_score":0.21449426,"about_ca_system_score_codex":0.00004171114,"about_ca_system_score_gemma":0.0002409246,"threshold_uncertainty_score":0.99974006},"labels":[],"label_agreement":null},{"id":"W2061741415","doi":"10.2478/amsc-2014-0022","title":"Application of GIS Methods in Assessing Effects of Mining Activity on Surface Infrastructure/Zastosowanie Metod Gis W Ocenie Wpływu Działalności Górniczej Na Infrastrukturę Na Powierzchni","year":2014,"lang":"en","type":"article","venue":"Archives of Mining Sciences","topic":"Geotechnical and Mining Engineering","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"University of New Brunswick","funders":"Politechnika Wrocławska","keywords":"Displacement (psychology); Data mining; Subsidence; Curvature; Field (mathematics); Geographic information system; Tilt (camera); Deformation (meteorology); Process (computing); Surface (topology); Geodesy; Geography; Computer science; Geology; Mathematics; Geotechnical engineering; Remote sensing; Mining engineering; Geometry; Geomorphology; Meteorology","score_opus":0.0091501194094984,"score_gpt":0.27956580270582315,"score_spread":0.27041568329632476,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2061741415","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.7998097,0.000125969,0.19767098,0.0000118757425,0.00015505575,0.00014506099,0.0000037621737,0.00008991823,0.0019877052],"genre_scores_gemma":[0.7287648,0.000010179341,0.27117077,0.000004613406,0.000015917089,0.000008009029,0.0000014063386,0.000020389263,0.0000039596844],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9981064,0.00016111278,0.0005479894,0.00040299862,0.00036733507,0.00041412617],"domain_scores_gemma":[0.9963184,0.0029194334,0.0002939845,0.00035349236,0.000026392247,0.00008830745],"candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00093944545,0.00028128855,0.000619815,0.00042837724,0.00007449895,0.00002556512,0.00058408245,0.00011212608,0.000003569433],"category_scores_gemma":[0.0008441191,0.00026140496,0.00011622461,0.0007665997,0.00043790386,0.00025975244,0.00013873947,0.00028353432,4.6696425e-7],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000010116771,0.000032499436,0.0044324505,0.0003629095,0.000022074377,4.9101686e-7,0.0014717908,0.315622,0.498585,0.00018192694,0.000004315449,0.17927445],"study_design_scores_gemma":[0.0003638794,0.00032201217,0.17648524,0.00073983456,0.000028052307,0.000003490308,0.0003331349,0.43500242,0.38600263,0.00038937686,0.000040179984,0.000289764],"about_ca_topic_score_codex":0.000056943863,"about_ca_topic_score_gemma":0.000005764495,"teacher_disagreement_score":0.17898469,"about_ca_system_score_codex":0.000027551641,"about_ca_system_score_gemma":0.00006172914,"threshold_uncertainty_score":0.9999838},"labels":[],"label_agreement":null},{"id":"W2409736007","doi":"10.1515/amsc-2015-0014","title":"Laboratory Method for Evaluating the Characteristics of Expansion Rock Bolts Subjected to Axial Tension / Laboratoryjna Metoda Badania Charakterystyk Kotew Rozprężnych Poddanych Rozciąganiu Osiowemu","year":2015,"lang":"en","type":"article","venue":"Archives of Mining Sciences","topic":"Structural Engineering and Materials Analysis","field":"Engineering","cited_by":22,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"","keywords":"Rock bolt; Rock mass classification; Structural engineering; Engineering; Tension (geology); Deformation (meteorology); Geotechnical engineering; Anchor bolt; Displacement (psychology); Geology; Compression (physics); Materials science; Composite material","score_opus":0.03152459710803243,"score_gpt":0.306393414485456,"score_spread":0.2748688173774235,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2409736007","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9754808,0.00020926552,0.023059832,0.00006889841,0.00069924555,0.00022730157,0.00009804677,0.00008928111,0.000067356756],"genre_scores_gemma":[0.8988941,0.000012106807,0.1008656,0.000029798968,0.00011911155,0.000021739535,0.000009354565,0.00002504699,0.000023175102],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99827695,0.00013818615,0.00052448886,0.00029967693,0.00043586662,0.00032481624],"domain_scores_gemma":[0.9985549,0.00064415426,0.00017068152,0.00028138974,0.00021850949,0.00013039199],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012673324,0.00021839808,0.0004820632,0.00023842366,0.00014237563,0.000046617988,0.0004460116,0.00005174249,0.000008923954],"category_scores_gemma":[0.0010561316,0.00015555747,0.00008511851,0.0006839454,0.00008184794,0.00012773953,0.00008862767,0.00007952732,0.000002265624],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000060213646,0.000008214703,0.00020339253,0.00009189403,0.000041851003,5.023174e-7,0.0031405468,0.026960121,0.96428037,0.00007343626,0.0001418378,0.0049976455],"study_design_scores_gemma":[0.0006594369,0.0010395909,0.018295314,0.00042540056,0.00017813379,0.000006595347,0.0027632033,0.47460046,0.5009352,0.00023594717,0.00035259774,0.00050810515],"about_ca_topic_score_codex":0.00004713031,"about_ca_topic_score_gemma":0.000009026883,"teacher_disagreement_score":0.46334514,"about_ca_system_score_codex":0.000019527723,"about_ca_system_score_gemma":0.00014185764,"threshold_uncertainty_score":0.634345},"labels":[],"label_agreement":null},{"id":"W2763991485","doi":"10.1515/amsc-2017-0047","title":"Stope Stability Assessment and Effect of Horizontal to Vertical Stress Ratio on the Yielding and Relaxation Zones Around Underground Open Stopes Using Empirical and Finite Element Methods","year":2017,"lang":"en","type":"article","venue":"Archives of Mining Sciences","topic":"Rock Mechanics and Modeling","field":"Engineering","cited_by":19,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; Western Canada Research Grid; Compute Canada","keywords":"Finite element method; Stability (learning theory); Geotechnical engineering; Structural engineering; Engineering; Graph; Mathematics; Computer science","score_opus":0.11227463433899432,"score_gpt":0.4107990698212014,"score_spread":0.2985244354822071,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2763991485","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9169107,0.000069931375,0.08226563,0.00016461297,0.000060855633,0.00020554823,0.00000281967,0.0000046813734,0.00031522583],"genre_scores_gemma":[0.9483149,0.00003231909,0.051623,0.0000076096508,0.000010210064,0.0000064152227,2.828228e-7,0.000004343925,9.317438e-7],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992143,0.00013693642,0.0001783608,0.00020532777,0.00013972969,0.00012532793],"domain_scores_gemma":[0.99797165,0.0017579972,0.000058981837,0.00015406685,0.000009111568,0.00004820191],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012878831,0.000090917834,0.00017882259,0.000049380164,0.0004716782,0.0002256733,0.0002197496,0.00001798668,0.0000011176718],"category_scores_gemma":[0.00029339216,0.00006106786,0.000014573696,0.00003381652,0.00018472645,0.00021867511,0.0003089047,0.00006673455,1.492124e-8],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00028455968,0.00012199955,0.28529224,0.0005483303,0.0001976892,0.0000027879587,0.023625297,0.1248406,0.29779512,0.031136855,0.000007705304,0.23614684],"study_design_scores_gemma":[0.00021641082,0.0008724071,0.027431501,0.00023532925,0.000024216131,0.0000012020657,0.0020813025,0.9425501,0.025418604,0.0010644883,0.0000041686994,0.00010024933],"about_ca_topic_score_codex":0.00006615624,"about_ca_topic_score_gemma":0.000070492344,"teacher_disagreement_score":0.8177095,"about_ca_system_score_codex":0.000011344132,"about_ca_system_score_gemma":0.000026916226,"threshold_uncertainty_score":0.3627815},"labels":[],"label_agreement":null},{"id":"W2780098508","doi":"10.1515/amsc-2017-0057","title":"Multivariate Linear Regression and CART Regression Analysis of TBM Performance at Abu Hamour Phase-I Tunnel","year":2017,"lang":"en","type":"article","venue":"Archives of Mining Sciences","topic":"Tunneling and Rock Mechanics","field":"Engineering","cited_by":16,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Geomechanica (Canada)","funders":"","keywords":"Linear regression; Multivariate statistics; Multivariate adaptive regression splines; Bayesian multivariate linear regression; Regression analysis; Regression; Cart; Statistics; Predictive modelling; Engineering; Geotechnical engineering; Mathematics; Mechanical engineering","score_opus":0.03270583821228161,"score_gpt":0.30569542406597155,"score_spread":0.27298958585368993,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2780098508","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9974754,0.0003796373,0.00062157615,0.000026424515,0.00016598585,0.00003680776,0.000011754189,0.000031836986,0.0012505694],"genre_scores_gemma":[0.9895667,0.00037417878,0.009848887,0.000001912185,0.000025282066,0.0000014992951,0.0000029227394,0.0000073314627,0.0001712889],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99913466,0.000022465942,0.00023612689,0.00021718573,0.00020309482,0.00018648393],"domain_scores_gemma":[0.9992523,0.00016550624,0.00020558432,0.0002962365,0.0000177236,0.000062633895],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00029003213,0.000120067976,0.000284385,0.00026379756,0.0005793064,0.000019763576,0.00036093243,0.000036956546,0.0000057453735],"category_scores_gemma":[0.00012353063,0.0000827042,0.00007339637,0.0001500264,0.00025866058,0.00015479643,0.00016160698,0.00007056018,5.6832494e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00012761894,0.000103281345,0.0840315,0.00034019983,0.00036617622,0.000006593379,0.024559185,0.134224,0.6274157,0.00015175772,0.0000860762,0.12858789],"study_design_scores_gemma":[0.0003514857,0.0001069109,0.04005826,0.0004769195,0.00009636421,0.0000017729443,0.00044109276,0.90020955,0.058089223,0.0000234248,0.00004163511,0.00010335188],"about_ca_topic_score_codex":0.00003593082,"about_ca_topic_score_gemma":0.00002589401,"teacher_disagreement_score":0.76598555,"about_ca_system_score_codex":0.000004606615,"about_ca_system_score_gemma":0.000015930134,"threshold_uncertainty_score":0.4455615},"labels":[],"label_agreement":null},{"id":"W2976836858","doi":"10.24425/ams.2019.128683","title":"Evaluation of Rockburst Potential in Kimberlite Using Fruit Fly Optimization Algorithm and Generalized Regression Neural Networks","year":2023,"lang":"en","type":"article","venue":"Archives of Mining Sciences","topic":"Rock Mechanics and Modeling","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Kimberlite; Artificial neural network; Regression; Regression analysis; Linear regression; Algorithm; Mining engineering; Engineering; Geology; Computer science; Artificial intelligence; Machine learning; Mathematics; Statistics; Geochemistry","score_opus":0.04335849993484894,"score_gpt":0.2908016126377845,"score_spread":0.24744311270293554,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2976836858","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.77732515,0.0004379561,0.22193803,0.000008112855,0.00014583835,0.00006283608,0.0000011614225,0.00001910878,0.0000617964],"genre_scores_gemma":[0.9276265,0.00019266327,0.072138734,0.0000017350998,0.000024856314,0.0000024790213,0.00000424809,0.000006398085,0.0000024234741],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991698,0.000059065624,0.00020512762,0.0001351585,0.00028822085,0.00014257376],"domain_scores_gemma":[0.99977744,0.000053622025,0.00006092981,0.00005779754,0.000027183542,0.000023052162],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006711369,0.00006652718,0.00011497091,0.00023551183,0.00007403413,0.000015716045,0.00008923324,0.000024124914,0.0000022874035],"category_scores_gemma":[0.00003234758,0.000060129445,0.000021890943,0.00030002842,0.00004217289,0.00012015973,0.000048556125,0.00003914255,3.150682e-8],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000020273185,0.0000023689804,0.00009305958,0.000007611404,0.0000035103487,3.6532683e-7,0.0007485234,0.91388255,0.0072287666,0.000010219433,0.0000012052282,0.07801981],"study_design_scores_gemma":[0.00025584147,0.000023473262,0.00040849744,0.00013104663,0.000016899927,0.0000014468952,0.00032689946,0.99763733,0.00084119383,0.0002959539,2.869723e-7,0.00006113844],"about_ca_topic_score_codex":0.000034197492,"about_ca_topic_score_gemma":0.0000065680083,"teacher_disagreement_score":0.1503013,"about_ca_system_score_codex":0.0000062682248,"about_ca_system_score_gemma":0.000022358225,"threshold_uncertainty_score":0.24520077},"labels":[],"label_agreement":null},{"id":"W4312062357","doi":"10.24425/ams.2020.134142","title":"A Preliminary Assessment of Climate Change Impacts – Implications for Mining Activity in Polish Coal Regions","year":2023,"lang":"en","type":"article","venue":"Archives of Mining Sciences","topic":"Geology and Environmental Impact Studies","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":false,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":true,"ca_institutions":"","funders":"Research Fund for Coal and Steel","keywords":"Climate change; Industrial chemistry; Coal; Environmental science; Coal mining; Environmental planning; Mining engineering; Engineering; Geology; Waste management; Biochemical engineering","score_opus":0.12146992320581393,"score_gpt":0.4152538020354332,"score_spread":0.2937838788296193,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4312062357","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97943693,0.00005577758,0.00004115972,0.005454818,0.00007217398,0.00025871137,0.000039523104,0.000021366357,0.014619549],"genre_scores_gemma":[0.99625283,0.00072419515,0.0028279384,0.000033475466,0.000029126433,0.00008396858,0.000002775023,0.0000032561172,0.00004245293],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99899906,0.000104623025,0.000166042,0.00018844195,0.00013370535,0.00040815346],"domain_scores_gemma":[0.9981562,0.0015174926,0.00016793518,0.00009449484,0.000007580185,0.000056322566],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000802272,0.00007101741,0.00017390637,0.0002261368,0.00062760705,0.0000098194005,0.0002593107,0.000031444386,0.000003582576],"category_scores_gemma":[0.0002888207,0.00006597189,0.00005826846,0.00040719265,0.0017990919,0.00023191729,0.00015141617,0.000041829357,4.912195e-7],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000022423903,0.00008969807,0.90924144,0.00003152405,0.0000110318415,4.6715934e-7,0.07399737,0.0001287947,0.00087666954,0.006071931,0.000081551974,0.009447075],"study_design_scores_gemma":[0.00013986866,0.00029719807,0.9679931,0.00008845557,0.000009379978,4.6650004e-7,0.028907502,0.0003724064,0.00007662633,0.0019981551,0.000052784853,0.0000640533],"about_ca_topic_score_codex":0.0007114146,"about_ca_topic_score_gemma":0.0013469342,"teacher_disagreement_score":0.058751643,"about_ca_system_score_codex":0.000015129009,"about_ca_system_score_gemma":0.000098336735,"threshold_uncertainty_score":0.6628829},"labels":[],"label_agreement":null},{"id":"W4362524302","doi":"10.24425/ams.2021.138598","title":"Application Cumulative Tensile Explosions for Roof Cutting in Chinese Underground Coal Mines","year":2023,"lang":"en","type":"article","venue":"Archives of Mining Sciences","topic":"Structural Response to Dynamic Loads","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Geomechanica (Canada)","funders":"National Key Research and Development Program of China; National Natural Science Foundation of China","keywords":"Roof; Coal mining; Mining engineering; Mine safety; Forensic engineering; Ultimate tensile strength; Industrial chemistry; Geology; Engineering; Geotechnical engineering; Coal; Structural engineering; Materials science; Metallurgy; Waste management","score_opus":0.025929746487507864,"score_gpt":0.30587311630688696,"score_spread":0.2799433698193791,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4362524302","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9943668,0.000051589013,0.0035829698,0.000109925284,0.00009910983,0.00017696357,0.0000101584355,0.00011658263,0.0014859054],"genre_scores_gemma":[0.9896793,0.000011277933,0.0100971535,0.000006125878,0.000028937222,0.00004763073,0.000008666651,0.000010554193,0.000110375484],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99921244,0.000021074044,0.00021142823,0.00018623892,0.00014000013,0.00022882354],"domain_scores_gemma":[0.9976381,0.0021709464,0.00004754541,0.00010179239,0.000010691667,0.00003089707],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00019712777,0.00009810154,0.00014373896,0.0003129469,0.0000984186,0.000016115271,0.00022472844,0.000020507996,0.0000020570467],"category_scores_gemma":[0.00041645044,0.0000804926,0.000041375082,0.00057000126,0.00021796278,0.00014146818,0.0000476939,0.000038652914,0.0000021162032],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005805428,0.000016981126,0.10145191,0.00013814481,0.000028082219,0.0000028389916,0.018692944,0.66512716,0.1555049,0.0020652798,0.00014174552,0.05677197],"study_design_scores_gemma":[0.00017835393,0.000039067723,0.14757854,0.00005625806,0.00000283313,0.0000018172593,0.0018533035,0.84360003,0.00078232214,0.0057821493,0.000032545227,0.00009279278],"about_ca_topic_score_codex":0.000026790594,"about_ca_topic_score_gemma":0.0000901046,"teacher_disagreement_score":0.17847288,"about_ca_system_score_codex":0.000012194015,"about_ca_system_score_gemma":0.000028733935,"threshold_uncertainty_score":0.3282393},"labels":[],"label_agreement":null},{"id":"W4384933328","doi":"10.24425/ams.2022.143680","title":"Preprocessing Large Datasets Using Gaussian Mixture Modelling to Improve Prediction Accuracy of Truck Productivity at Mine Sites","year":2023,"lang":"en","type":"article","venue":"Archives of Mining Sciences","topic":"Mineral Processing and Grinding","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Alberta Environment and Protected Areas","funders":"","keywords":"Truck; Productivity; Preprocessor; Gaussian; Data mining; Engineering; Computer science; Environmental science; Artificial intelligence; Automotive engineering; Chemistry; Economics","score_opus":0.036250004304845033,"score_gpt":0.2867522487309388,"score_spread":0.25050224442609376,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4384933328","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.99276173,0.00022247179,0.0057877754,0.000042054828,0.00016683342,0.00012953814,0.0002568224,0.00014436476,0.0004884101],"genre_scores_gemma":[0.97436965,0.000013079022,0.025367068,0.0000041731478,0.00009808983,0.0000054757984,0.000047812468,0.00001677908,0.0000779053],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9985491,0.000027759834,0.00033706438,0.0004157237,0.0002866127,0.00038374533],"domain_scores_gemma":[0.9992764,0.00026177213,0.00013763775,0.00022545001,0.00001952728,0.000079215],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00053602445,0.00015920242,0.0002329365,0.00036302727,0.00029782177,0.00004253423,0.0003077732,0.000036680074,0.0000044987096],"category_scores_gemma":[0.00029991422,0.00014193755,0.000045414705,0.0008221684,0.00016991807,0.00045079243,0.00017001877,0.000094037874,0.0000017153192],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00001351921,0.000013179972,0.012234714,0.00040664058,0.000012456413,0.0000010532381,0.004894941,0.68689334,0.2918516,0.000011022815,0.000107195985,0.003560303],"study_design_scores_gemma":[0.00013621582,0.00006584976,0.003085843,0.00050486304,0.00001867107,0.000005375623,0.00069565774,0.945565,0.049504615,0.00017849628,0.000075527016,0.00016390756],"about_ca_topic_score_codex":0.000021526823,"about_ca_topic_score_gemma":0.000017427614,"teacher_disagreement_score":0.2586716,"about_ca_system_score_codex":0.00001475795,"about_ca_system_score_gemma":0.000046507237,"threshold_uncertainty_score":0.57880455},"labels":[],"label_agreement":null}]}