{"meta":{"query_hash":"4173ac8a0bac","filters":{"venue":"Quantitative geology and geostatistics"},"cohort_total":37,"direct_labels_cover":0,"predictions_cover":37,"exported":37,"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/4173ac8a0bac","api":"https://metacan.xera.ac/api/v1/cohort?venue=Quantitative+geology+and+geostatistics"},"results":[{"id":"W1019458194","doi":"10.1007/978-1-4020-3610-1_41","title":"A Non-linear GPR Tomographic Inversion Algorithm Based on Iterated Cokriging and Conditional Simulations","year":2005,"lang":"en","type":"book-chapter","venue":"Quantitative geology and geostatistics","topic":"Geophysical Methods and Applications","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Ground-penetrating radar; Inversion (geology); Iterated function; Algorithm; Geology; Computer science; Mathematics; Seismology; Mathematical analysis","score_opus":0.01946512640467433,"score_gpt":0.280942128276992,"score_spread":0.26147700187231765,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1019458194","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0020838673,0.000020502894,0.9968449,0.000020730338,0.000010947763,0.000014843164,0.00001583507,0.0005625492,0.00042584026],"genre_scores_gemma":[0.04339656,0.000047381083,0.9547541,0.000029148909,0.000011589727,0.00007711096,0.000112163056,0.00020249184,0.0013695463],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99975365,0.000067030334,0.00001504289,0.000042436026,0.00010384475,0.000018002967],"domain_scores_gemma":[0.99929047,0.0003684384,0.000035073936,0.00009729613,0.00018534905,0.000023377765],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00059358764,0.00054145965,0.00084373384,0.0003570091,0.00041504425,0.0006378739,0.0015490502,0.000753032,0.0028207963],"category_scores_gemma":[0.001785145,0.00057778106,0.0006782099,0.00058983755,0.00046418735,0.00083644805,0.0009154432,0.001156722,0.0010183069],"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":[0.00014341039,0.00010928216,0.0006190594,0.00010638315,0.0000884518,0.000102396116,0.00011174469,0.66215646,0.015908208,0.025472268,0.0028661569,0.29231614],"study_design_scores_gemma":[0.000006718617,0.000009048702,0.00006561,0.000002099648,0.000005180261,0.000029811394,0.0000025706784,0.9967981,0.0010451808,0.0014957425,0.00053325144,0.0000066619723],"about_ca_topic_score_codex":0.0059480797,"about_ca_topic_score_gemma":0.009365397,"teacher_disagreement_score":0.0059480797,"about_ca_system_score_codex":0.00045006667,"about_ca_system_score_gemma":0.0011445176,"threshold_uncertainty_score":0.011826873},"labels":[],"label_agreement":null},{"id":"W110051228","doi":"10.1007/978-1-4020-3610-1_30","title":"Geostatistical Simulation of Fracture Networks","year":2005,"lang":"en","type":"book-chapter","venue":"Quantitative geology and geostatistics","topic":"Groundwater flow and contamination studies","field":"Environmental Science","cited_by":25,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Power Generation","funders":"","keywords":"Lineament; Probabilistic logic; Fracture (geology); Property (philosophy); Geology; Field (mathematics); Computer science; Ideal (ethics); Geotechnical engineering; Artificial intelligence; Mathematics; Seismology","score_opus":0.01743083287270604,"score_gpt":0.26854254120128185,"score_spread":0.2511117083285758,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W110051228","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.065226115,0.00032576002,0.91036004,0.00080746884,0.000110333545,0.000098026336,0.0016319767,0.0025243114,0.018916044],"genre_scores_gemma":[0.6413943,0.0005647292,0.34704047,0.0002259338,0.00008363898,0.00048567928,0.0016824718,0.0006543144,0.007868444],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99963176,0.00015962616,0.000024274652,0.000041564632,0.00011131741,0.00003136066],"domain_scores_gemma":[0.99740285,0.0019571695,0.000109488836,0.00016064405,0.00030834405,0.00006145453],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00081602857,0.00046969252,0.0008462685,0.000721462,0.00060008385,0.0010714388,0.0016897283,0.0013824411,0.006196304],"category_scores_gemma":[0.004224264,0.00066148594,0.0008416445,0.0013239338,0.0007284498,0.0008110981,0.000839834,0.0010462243,0.0006263524],"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":[0.000012721081,0.000013259431,0.00032121537,0.000016980724,0.000009639076,0.000018032171,0.000026295345,0.981831,0.000149336,0.013047815,0.00066992315,0.0038836922],"study_design_scores_gemma":[0.000004324316,0.0000015078087,0.00003226467,0.0000019298836,0.0000012316661,0.0000039827323,0.000003202777,0.9952068,0.00007116594,0.0043448964,0.00032719658,0.0000015111831],"about_ca_topic_score_codex":0.02528925,"about_ca_topic_score_gemma":0.017666271,"teacher_disagreement_score":0.02528925,"about_ca_system_score_codex":0.0010069113,"about_ca_system_score_gemma":0.0017382618,"threshold_uncertainty_score":0.050284088},"labels":[],"label_agreement":null},{"id":"W113501221","doi":"10.1007/978-1-4020-6448-7_30","title":"Temporal Geostatistical Analyses of N2O Fluxes from Differently Treated Soils","year":2008,"lang":"en","type":"book-chapter","venue":"Quantitative geology and geostatistics","topic":"Soil Geostatistics and Mapping","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Environmental science; Soil water; Spatial variability; Soil science; Flux (metallurgy); Geostatistics; Data set; Series (stratigraphy); Atmospheric sciences; Sill; Exponential function; Hydrology (agriculture); Mathematics; Statistics; Geology; Chemistry; Geotechnical engineering","score_opus":0.058825098299577064,"score_gpt":0.30548969485295774,"score_spread":0.2466645965533807,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W113501221","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.87606364,0.00033938067,0.10762109,0.00011782944,0.00006378411,0.000044651417,0.00997805,0.0011635318,0.0046079885],"genre_scores_gemma":[0.9175837,0.0002554886,0.06739831,0.00004599946,0.000030642947,0.00010619375,0.011258766,0.000325284,0.0029956538],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997464,0.00004327153,0.000020663654,0.00008595696,0.000076960256,0.000026830672],"domain_scores_gemma":[0.99954224,0.00025420132,0.00006136976,0.000047179554,0.00008252984,0.000012415993],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00042361027,0.000244408,0.0001969261,0.0009105704,0.00023773953,0.00045511455,0.00034019625,0.00016846422,0.0014415414],"category_scores_gemma":[0.00091450044,0.00013793318,0.00063387834,0.0015909547,0.0001763139,0.0003467268,0.00027931985,0.00025499304,0.00020325482],"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":[0.002354089,0.00041550852,0.20142443,0.00068464363,0.0013430808,0.0005556296,0.0009919576,0.07338533,0.2989112,0.012565396,0.009979325,0.39738938],"study_design_scores_gemma":[0.00005954267,0.00029335462,0.6463951,0.000029271714,0.00043631726,0.0008293257,0.0014344072,0.23929924,0.08710457,0.01171106,0.012278761,0.0001290044],"about_ca_topic_score_codex":0.009534727,"about_ca_topic_score_gemma":0.015816424,"teacher_disagreement_score":0.009534727,"about_ca_system_score_codex":0.00039903825,"about_ca_system_score_gemma":0.00044988244,"threshold_uncertainty_score":0.01895845},"labels":[],"label_agreement":null},{"id":"W115957074","doi":"10.1007/978-3-319-06874-9_11","title":"Multifractals and Local Singularity Analysis","year":2014,"lang":"en","type":"book-chapter","venue":"Quantitative geology and geostatistics","topic":"Geochemistry and Geologic Mapping","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Geological Survey of Canada; Natural Resources Canada","funders":"","keywords":"Multifractal system; Singularity; Fractal; Fractal dimension; Mathematics; Measure (data warehouse); Statistical physics; Histogram; Statistics; Mathematical analysis; Physics; Image (mathematics)","score_opus":0.020918153032006944,"score_gpt":0.26095751184885296,"score_spread":0.24003935881684602,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W115957074","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.025818381,0.051064584,0.84137195,0.0030191762,0.0010058979,0.000024439869,0.00022019033,0.0005190261,0.07695636],"genre_scores_gemma":[0.64941573,0.03305484,0.19284685,0.00085180573,0.004976119,0.000085644,0.0004830147,0.0006360642,0.11765002],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9997569,0.000075403215,0.000012476744,0.00004071397,0.00009812624,0.000016448927],"domain_scores_gemma":[0.999433,0.00029456426,0.00006287104,0.00006141973,0.000116154355,0.00003189977],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005037608,0.00073343585,0.00069161766,0.002123936,0.00038658822,0.0013007988,0.000446406,0.0006639982,0.004225203],"category_scores_gemma":[0.0023197322,0.00025624427,0.00041805554,0.0017903391,0.0014086397,0.001667803,0.0007802113,0.001409632,0.0008918836],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.0000073733954,0.000010290615,0.00016848529,0.000076472956,0.00001813804,0.00006137507,0.00012639392,0.0073919133,0.0008513133,0.9108956,0.0114094,0.0689832],"study_design_scores_gemma":[0.0000023954692,0.000007197021,0.0004207643,0.00002111815,0.000008305949,0.000102189915,0.000033341526,0.034681335,0.00022431806,0.94650596,0.017979335,0.000013688842],"about_ca_topic_score_codex":0.001240644,"about_ca_topic_score_gemma":0.0010860639,"teacher_disagreement_score":0.004225203,"about_ca_system_score_codex":0.0005773123,"about_ca_system_score_gemma":0.00025472674,"threshold_uncertainty_score":0.014134705},"labels":[],"label_agreement":null},{"id":"W122534238","doi":"10.1007/978-1-4020-3610-1_65","title":"Preservation of Multiple Point Structure when Conditioning by Kriging","year":2005,"lang":"en","type":"book-chapter","venue":"Quantitative geology and geostatistics","topic":"Advanced Multi-Objective Optimization Algorithms","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Kriging; Categorical variable; Conditioning; Variogram; Range (aeronautics); Mathematics; Statistics; Mathematical optimization; Computer science; Algorithm; Applied mathematics; Engineering","score_opus":0.016053441515165322,"score_gpt":0.2635232030837113,"score_spread":0.24746976156854597,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W122534238","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0045208638,0.00009415359,0.9945305,0.00003441255,0.000017698174,0.000007770369,0.000039908602,0.00023885998,0.00051575754],"genre_scores_gemma":[0.27169937,0.0007563954,0.72063285,0.0001111144,0.000087825996,0.000081832775,0.00037791595,0.0009821408,0.00527057],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99858534,0.0005111578,0.00007423615,0.00025073512,0.00047710168,0.00010144267],"domain_scores_gemma":[0.99408466,0.0032071832,0.00027329515,0.0019391427,0.00042038047,0.00007543004],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002397781,0.00092392205,0.0014271548,0.00063598936,0.00048007455,0.001225421,0.001431372,0.0007125,0.0032550446],"category_scores_gemma":[0.012411698,0.0010967499,0.00087938627,0.0017166515,0.0019298843,0.0024887032,0.0019430639,0.0021259675,0.0009139738],"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":[0.00024248922,0.000080895865,0.0017518994,0.00041588067,0.000118607844,0.00021124554,0.00030251822,0.49120238,0.02529474,0.11903328,0.0027288185,0.3586172],"study_design_scores_gemma":[0.0000113995175,0.00005506365,0.0010823559,0.000022210352,0.000039141833,0.00015595589,0.000028619654,0.8823013,0.022997815,0.08969908,0.003579384,0.000027636115],"about_ca_topic_score_codex":0.0025505484,"about_ca_topic_score_gemma":0.003895054,"teacher_disagreement_score":0.0032550446,"about_ca_system_score_codex":0.00046954147,"about_ca_system_score_gemma":0.00087824493,"threshold_uncertainty_score":0.012680829},"labels":[],"label_agreement":null},{"id":"W129351944","doi":"10.1007/978-1-4020-3610-1_9","title":"Direct Geostatistical Simulation on Unstructured Grids","year":2005,"lang":"en","type":"book-chapter","venue":"Quantitative geology and geostatistics","topic":"Soil Geostatistics and Mapping","field":"Environmental Science","cited_by":6,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Kriging; Homoscedasticity; Grid; Unstructured grid; Computer science; Gaussian; Block (permutation group theory); Heteroscedasticity; Algorithm; Variance (accounting); Variogram; Mathematical optimization; Applied mathematics; Mathematics; Accounting; Geometry; Machine learning; Chemistry","score_opus":0.02244818937905155,"score_gpt":0.2783490264179396,"score_spread":0.25590083703888805,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W129351944","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0091282455,0.0001346483,0.971778,0.00016275022,0.00007540001,0.0000638998,0.00026613343,0.0012536194,0.017137373],"genre_scores_gemma":[0.30716872,0.00043876338,0.65715045,0.00024962806,0.00010978131,0.00046652518,0.0010372937,0.0011546097,0.032224316],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996371,0.0001298604,0.000016807724,0.000043682314,0.00014906681,0.000023413255],"domain_scores_gemma":[0.99841166,0.0010373167,0.00004941199,0.00023385948,0.00022086789,0.000046874015],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004873001,0.0005347105,0.0007766115,0.0002727245,0.00040820517,0.0008663359,0.0012028895,0.0009152967,0.009207699],"category_scores_gemma":[0.003181741,0.0006046152,0.00059756485,0.000490068,0.0006383422,0.0007758582,0.0014170463,0.000969302,0.0018422261],"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":[0.000034695964,0.000027701319,0.0003982074,0.000077122226,0.000024129857,0.00008813743,0.000091566646,0.9307838,0.0011832954,0.037121937,0.0053700306,0.024799496],"study_design_scores_gemma":[0.00001553901,0.000004418218,0.000030874286,0.0000040746886,0.0000023236591,0.000019235476,0.000006329011,0.9834351,0.00040184107,0.013069713,0.0030076064,0.000003008226],"about_ca_topic_score_codex":0.0061768377,"about_ca_topic_score_gemma":0.00543258,"teacher_disagreement_score":0.009207699,"about_ca_system_score_codex":0.0004752598,"about_ca_system_score_gemma":0.00084150175,"threshold_uncertainty_score":0.030802786},"labels":[],"label_agreement":null},{"id":"W13295998","doi":"10.1007/978-1-4020-3610-1_55","title":"Implementation Aspects of Sequential Simulation","year":2005,"lang":"en","type":"book-chapter","venue":"Quantitative geology and geostatistics","topic":"Soil Geostatistics and Mapping","field":"Environmental Science","cited_by":12,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Ergodic theory; Construct (python library); Computer science; Gaussian; Path (computing); Affect (linguistics); Algorithm; Industrial engineering; Mathematical optimization; Management science; Operations research; Mathematics; Engineering; Psychology","score_opus":0.0331810624338451,"score_gpt":0.3198144782780529,"score_spread":0.2866334158442078,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W13295998","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00993025,0.00017102469,0.9675189,0.00069540413,0.00008800155,0.000058390342,0.000056713157,0.00084552134,0.02063577],"genre_scores_gemma":[0.50828975,0.00045701285,0.47323307,0.00052559236,0.00021638443,0.0003450178,0.00039790044,0.00074623275,0.015789067],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99580115,0.0018127776,0.00022880705,0.0005166342,0.0013176973,0.0003230025],"domain_scores_gemma":[0.99094135,0.0055836793,0.00026060705,0.002047073,0.000989762,0.00017749298],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0032547151,0.0006551994,0.0006247896,0.00034306542,0.00075466087,0.0022888158,0.0017131428,0.0010260253,0.016256722],"category_scores_gemma":[0.022028305,0.00062079524,0.0006603946,0.001043386,0.0012712526,0.0032850965,0.0018227171,0.0017697377,0.0023812368],"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":[0.00043440904,0.00017937121,0.002450551,0.0001770392,0.00007067605,0.00017911906,0.00035778218,0.14981575,0.0034383663,0.6528207,0.010102009,0.17997417],"study_design_scores_gemma":[0.000066587134,0.000049475664,0.00026835717,0.00001962537,0.000029273326,0.00013593429,0.000054217002,0.604797,0.0027564089,0.37741584,0.014396054,0.00001129648],"about_ca_topic_score_codex":0.0036679371,"about_ca_topic_score_gemma":0.0028953392,"teacher_disagreement_score":0.016256722,"about_ca_system_score_codex":0.000848063,"about_ca_system_score_gemma":0.0020682022,"threshold_uncertainty_score":0.054384172},"labels":[],"label_agreement":null},{"id":"W133870503","doi":"10.1007/978-3-319-06874-9_9","title":"Quantitative Stratigraphy, Splining and Geologic Time Scales","year":2014,"lang":"en","type":"book-chapter","venue":"Quantitative geology and geostatistics","topic":"earthquake and tectonic studies","field":"Earth and Planetary Sciences","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Geological Survey of Canada; Natural Resources Canada","funders":"","keywords":"Stratigraphy; Geology; Geologic time scale; Physical geography; Paleontology; Geography; Sedimentary rock","score_opus":0.02793642649270288,"score_gpt":0.24949947371242812,"score_spread":0.22156304721972525,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W133870503","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.060641,0.043460958,0.65250224,0.0038745324,0.000784359,0.000079165526,0.0031440214,0.0011232633,0.23439045],"genre_scores_gemma":[0.5785959,0.027830575,0.19187751,0.0006864269,0.00086281745,0.00014467289,0.0024957967,0.000886534,0.1966198],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996779,0.000056846064,0.000015469413,0.000092604205,0.00014092016,0.00001623362],"domain_scores_gemma":[0.99912363,0.0004836106,0.000108224966,0.00011358169,0.00014397809,0.000026883863],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00072108576,0.00053825154,0.00027900471,0.0010803867,0.00017922063,0.0023275998,0.0006966614,0.00049407315,0.007682052],"category_scores_gemma":[0.003535342,0.00041580028,0.00026365655,0.0019190557,0.0016062695,0.0027104162,0.00044588948,0.0011715061,0.0012013665],"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":[0.000030740124,0.000028183014,0.003976376,0.00039253134,0.000032269894,0.000042129635,0.0005247888,0.013145895,0.0059103896,0.7138017,0.0122959325,0.24981914],"study_design_scores_gemma":[0.0000070378874,0.000046413574,0.016247924,0.0001307046,0.000030505342,0.0001913402,0.00042323058,0.03343074,0.0031649228,0.8184609,0.12783241,0.000033757995],"about_ca_topic_score_codex":0.0029164874,"about_ca_topic_score_gemma":0.004325368,"teacher_disagreement_score":0.007682052,"about_ca_system_score_codex":0.0010092268,"about_ca_system_score_gemma":0.0006812305,"threshold_uncertainty_score":0.02569902},"labels":[],"label_agreement":null},{"id":"W138014484","doi":"10.1007/978-94-007-4153-9_14","title":"Applications of Data Coherency for Data Analysis and Geological Zonation","year":2012,"lang":"en","type":"book-chapter","venue":"Quantitative geology and geostatistics","topic":"Geological Modeling and Analysis","field":"Earth and Planetary Sciences","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Facies; Cluster analysis; Data mining; Geology; Similarity (geometry); Metric (unit); Quality (philosophy); Data quality; Measure (data warehouse); Computer science; Image (mathematics); Artificial intelligence; Engineering; Paleontology","score_opus":0.12707749668835025,"score_gpt":0.3297860696180339,"score_spread":0.20270857292968367,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W138014484","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.001429048,0.011217139,0.96814203,0.00089011766,0.0005603584,0.0000625687,0.00030145122,0.00077156274,0.016625647],"genre_scores_gemma":[0.0399247,0.0116056595,0.93646866,0.00033494545,0.0007956009,0.00019744622,0.0007149586,0.0007343457,0.009223791],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9968928,0.0010493533,0.00030645516,0.00046994135,0.0012081057,0.00007321304],"domain_scores_gemma":[0.993083,0.004983439,0.00018465957,0.00084488146,0.0008317304,0.00007217125],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0042717094,0.0014049038,0.00094632513,0.0040397965,0.00049583503,0.0041534817,0.0012932318,0.0008740154,0.0076307836],"category_scores_gemma":[0.016849384,0.00091714214,0.0009946722,0.0073565054,0.0021603957,0.0039387937,0.0027435736,0.002229344,0.0022609646],"study_design_candidate":"not_applicable","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":[0.000033612705,0.000020318617,0.00096852606,0.00047141817,0.00011069013,0.000108796165,0.0005402306,0.0077480306,0.002397781,0.4506904,0.018572362,0.51833785],"study_design_scores_gemma":[0.000017275832,0.000032679975,0.0013739497,0.0002479241,0.00006797471,0.00037922617,0.0002850386,0.07104041,0.004576861,0.6862622,0.23565663,0.000059808564],"about_ca_topic_score_codex":0.0021348586,"about_ca_topic_score_gemma":0.0026344403,"teacher_disagreement_score":0.0076307836,"about_ca_system_score_codex":0.0007996945,"about_ca_system_score_gemma":0.000990015,"threshold_uncertainty_score":0.025527537},"labels":[],"label_agreement":null},{"id":"W151458526","doi":"10.1007/978-94-007-4153-9_7","title":"Modeling Nonlinear Beta Probability Fields","year":2012,"lang":"en","type":"book-chapter","venue":"Quantitative geology and geostatistics","topic":"Gaussian Processes and Bayesian Inference","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Victoria","funders":"","keywords":"BETA (programming language); Nonlinear system; Statistical physics; Mathematics; Computer science; Physics; Quantum mechanics","score_opus":0.043728161284140095,"score_gpt":0.2756271903406014,"score_spread":0.23189902905646131,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W151458526","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.01496405,0.00057744497,0.9775745,0.0002684762,0.000048134207,0.000010761047,0.00008505763,0.00020807575,0.0062634842],"genre_scores_gemma":[0.6753599,0.0034611674,0.27501687,0.00023270078,0.0002969481,0.00019324129,0.0008266348,0.00046881963,0.044143725],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9997607,0.000098821656,0.000009538957,0.00004838363,0.000060369824,0.000022152952],"domain_scores_gemma":[0.9988788,0.0007850033,0.000100887635,0.00009119786,0.00009896054,0.00004515874],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00095161446,0.00065570226,0.0007076204,0.00043562416,0.00029692907,0.0011896669,0.0011037966,0.0010003782,0.0027928783],"category_scores_gemma":[0.004270162,0.00060629525,0.00069577264,0.0007731856,0.0007712903,0.0015800882,0.0011141957,0.0010429954,0.00061427016],"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":[0.000027711169,0.000023412402,0.00060878415,0.000048711812,0.000029976463,0.000069298774,0.000081835235,0.7848433,0.0009356998,0.18343021,0.0017911975,0.028109865],"study_design_scores_gemma":[0.0000027966817,0.0000037838954,0.00007213686,0.0000045724487,0.0000042972083,0.000021375678,0.0000055113983,0.91593796,0.00014518628,0.08261266,0.001185068,0.0000045778415],"about_ca_topic_score_codex":0.004354323,"about_ca_topic_score_gemma":0.0029734178,"teacher_disagreement_score":0.004354323,"about_ca_system_score_codex":0.0007192619,"about_ca_system_score_gemma":0.0004909966,"threshold_uncertainty_score":0.009343088},"labels":[],"label_agreement":null},{"id":"W174032269","doi":"10.1007/978-94-010-0810-5_18","title":"Stochastic Flow and Transport Simulations of a Three-Dimensional Tracer Test in Moderately Fractured Plutonic Rock","year":2001,"lang":"en","type":"book-chapter","venue":"Quantitative geology and geostatistics","topic":"Groundwater flow and contamination studies","field":"Environmental Science","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Ontario Power Generation; Atomic Energy (Canada)","funders":"","keywords":"Pluton; Permeability (electromagnetism); Geology; Porosity; TRACER; Flow (mathematics); Geotechnical engineering; Petrology; Seismology; Mechanics","score_opus":0.021533069829355083,"score_gpt":0.2494571174578153,"score_spread":0.22792404762846022,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W174032269","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9743484,0.00014464512,0.02021419,0.00042288634,0.00003854642,0.00003430826,0.0006726193,0.00027838672,0.003846035],"genre_scores_gemma":[0.9936632,0.000057325364,0.004610578,0.00003962822,0.000011328778,0.000026914275,0.00034809555,0.000043155567,0.0011996557],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998343,0.000051382496,0.000012460561,0.00003137629,0.000025101965,0.000045280205],"domain_scores_gemma":[0.9972338,0.0021412259,0.00016586509,0.00008031955,0.00020211909,0.00017671086],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006644536,0.00048824114,0.0007174555,0.0007378584,0.00097501965,0.0009558361,0.0015711301,0.0018729613,0.0024122843],"category_scores_gemma":[0.0029595697,0.0005701434,0.0008273606,0.00091807946,0.0015859463,0.00072131597,0.0006123964,0.0010764396,0.000105438725],"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":[0.000050960538,0.00004397449,0.0012330463,0.000008329486,0.000007894876,0.000032485634,0.000033324366,0.99523973,0.00033021122,0.0023246547,0.00017282164,0.0005225741],"study_design_scores_gemma":[0.0000095514215,0.000007019609,0.00019534213,8.7934893e-7,0.0000019035028,0.000002468991,0.000005837753,0.99936336,0.00011713963,0.00027409315,0.000019723364,0.0000027219576],"about_ca_topic_score_codex":0.113416776,"about_ca_topic_score_gemma":0.046354894,"teacher_disagreement_score":0.113416776,"about_ca_system_score_codex":0.0025655157,"about_ca_system_score_gemma":0.0016460543,"threshold_uncertainty_score":0.22551328},"labels":[],"label_agreement":null},{"id":"W17988514","doi":"10.1007/978-1-4020-3610-1_14","title":"Conditioning Event-based Fluvial Models","year":2005,"lang":"en","type":"book-chapter","venue":"Quantitative geology and geostatistics","topic":"Reservoir Engineering and Simulation Methods","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Fluvial; Streamlines, streaklines, and pathlines; Event (particle physics); Sedimentary depositional environment; Geology; Confusion; Computer science; Paleontology; Engineering; Structural basin","score_opus":0.03250349609544773,"score_gpt":0.2915819478986728,"score_spread":0.2590784518032251,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W17988514","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.09488464,0.00025656167,0.89749974,0.0003630953,0.00013088166,0.00006472874,0.0005178734,0.0012007895,0.0050817537],"genre_scores_gemma":[0.9499733,0.0004427007,0.04223929,0.00014683136,0.00009887252,0.0001358945,0.0008864042,0.00017336507,0.005903382],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991365,0.00033615567,0.000047801987,0.000191512,0.00017877082,0.0001093464],"domain_scores_gemma":[0.99490535,0.0039073196,0.00026796068,0.00044926954,0.000359573,0.000110542016],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0027398602,0.0006799168,0.00097020896,0.00046351043,0.0003140455,0.00094087975,0.0017646687,0.0010201698,0.006841156],"category_scores_gemma":[0.010173239,0.0006454265,0.0006552094,0.00054830126,0.0010213655,0.0017127808,0.0015012302,0.0017381841,0.00045562023],"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":[0.00007129596,0.000048657792,0.0013115691,0.000023558494,0.000044024648,0.000029369701,0.00003434013,0.9630241,0.00043599622,0.02518423,0.0006535335,0.009139343],"study_design_scores_gemma":[0.000006756422,0.0000071335435,0.00011985036,0.0000020569225,0.0000068764602,0.000004723013,0.0000025457346,0.99002683,0.0002956497,0.0093950555,0.00012908774,0.000003469166],"about_ca_topic_score_codex":0.0068375967,"about_ca_topic_score_gemma":0.006601476,"teacher_disagreement_score":0.006841156,"about_ca_system_score_codex":0.0007407283,"about_ca_system_score_gemma":0.0008562123,"threshold_uncertainty_score":0.022885919},"labels":[],"label_agreement":null},{"id":"W1997913929","doi":"10.1007/978-1-4020-3610-1_80","title":"Local Updating of Reservoir Properties for Production Data Integration","year":2005,"lang":"en","type":"book-chapter","venue":"Quantitative geology and geostatistics","topic":"Reservoir Engineering and Simulation Methods","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Kriging; Property (philosophy); Permeability (electromagnetism); Sensitivity (control systems); Mathematical optimization; Production (economics); Iterative and incremental development; Computer science; Reservoir simulation; Petroleum engineering; Production rate; Process (computing); Physical property; Point (geometry); Applied mathematics; Algorithm; Mathematics; Geology; Engineering; Industrial engineering; Materials science; Geometry; Machine learning","score_opus":0.09283884507759815,"score_gpt":0.32470102009157165,"score_spread":0.2318621750139735,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1997913929","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.013179131,0.00019997127,0.9809239,0.00006837445,0.00004459469,0.000020031968,0.00024911735,0.0036311925,0.0016837422],"genre_scores_gemma":[0.45900443,0.0003436211,0.5345729,0.000071192706,0.000085451626,0.00009434542,0.00088776136,0.0011301661,0.0038100828],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995925,0.000106853586,0.00003149706,0.00011402732,0.00012943632,0.00002574766],"domain_scores_gemma":[0.99854183,0.0003764782,0.000105903026,0.00061300915,0.00032320985,0.000039521023],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010613858,0.0004970322,0.000877973,0.0007204692,0.0003625377,0.0013372246,0.0013086213,0.0004556244,0.0039537787],"category_scores_gemma":[0.0039608288,0.00053191156,0.0005722719,0.0013640658,0.0003814106,0.00221172,0.001192493,0.00087971357,0.0012194011],"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":[0.00022321781,0.00012775655,0.004778316,0.00021328252,0.00011098623,0.000100889636,0.00021901417,0.38447952,0.02305692,0.00948843,0.009440187,0.5677615],"study_design_scores_gemma":[0.000015805424,0.000025947296,0.0011799316,0.000013164657,0.0000314544,0.000051636227,0.000022953636,0.97477597,0.015485059,0.0035154584,0.0048627323,0.000019838666],"about_ca_topic_score_codex":0.0046568755,"about_ca_topic_score_gemma":0.00896189,"teacher_disagreement_score":0.0046568755,"about_ca_system_score_codex":0.00049020274,"about_ca_system_score_gemma":0.0006357405,"threshold_uncertainty_score":0.0132267475},"labels":[],"label_agreement":null},{"id":"W202249359","doi":"10.1007/978-94-017-1701-4_12","title":"Successful Incorporation of Geological Controls into Reserve Evaluation: Recent Examples from Giant Copper Mines in Chile","year":2002,"lang":"en","type":"book-chapter","venue":"Quantitative geology and geostatistics","topic":"Mining Techniques and Economics","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"PricewaterhouseCoopers (Canada)","funders":"","keywords":"Boom; Copper mine; Mining engineering; Copper ore; Estimation; Presentation (obstetrics); Geology; Engineering; Copper; Oceanography; Systems engineering; Chemistry","score_opus":0.06089361003180653,"score_gpt":0.27875581583276293,"score_spread":0.2178622058009564,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W202249359","genre_codex":"empirical","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.865731,0.0037877832,0.014524786,0.007352767,0.000078712554,0.00024647516,0.00052458706,0.00019389944,0.10755988],"genre_scores_gemma":[0.9793305,0.0010750871,0.0071696467,0.00016806096,0.00002514965,0.000046184465,0.0001346506,0.000040232742,0.012010506],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9989452,0.00039966524,0.000057432568,0.00007655131,0.00036981155,0.00015150975],"domain_scores_gemma":[0.9948133,0.0027936047,0.0005334476,0.00041587945,0.0012453423,0.0001984081],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0028053469,0.00027224104,0.00028598733,0.001136942,0.0012062765,0.0017090905,0.0010078168,0.00061661063,0.0017644789],"category_scores_gemma":[0.0084841475,0.00019790302,0.00021057062,0.0029643239,0.0020126041,0.00095161406,0.0019769997,0.0007367493,0.00018461955],"study_design_candidate":"not_applicable","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":[0.0003996346,0.00041194737,0.24032287,0.001019371,0.00012871354,0.0040766266,0.02132219,0.027038082,0.0043718927,0.05989205,0.028786208,0.6122305],"study_design_scores_gemma":[0.00016447932,0.0005136561,0.58991283,0.0007345595,0.00018832488,0.0014933789,0.042709243,0.02756234,0.012653516,0.026664782,0.2971652,0.0002376104],"about_ca_topic_score_codex":0.10405394,"about_ca_topic_score_gemma":0.24864465,"teacher_disagreement_score":0.10405394,"about_ca_system_score_codex":0.0043966235,"about_ca_system_score_gemma":0.003993365,"threshold_uncertainty_score":0.20689654},"labels":[],"label_agreement":null},{"id":"W2115088602","doi":"10.1007/978-94-007-4153-9_22","title":"Non-random Discrete Fracture Network Modeling","year":2012,"lang":"en","type":"book-chapter","venue":"Quantitative geology and geostatistics","topic":"Groundwater flow and contamination studies","field":"Environmental Science","cited_by":5,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Fracture (geology); Orientation (vector space); Centroid; Poisson distribution; Geology; Rock mass classification; Computer science; Algorithm; Geometry; Statistics; Geotechnical engineering; Mathematics; Artificial intelligence","score_opus":0.01881807489499374,"score_gpt":0.2521438273019144,"score_spread":0.2333257524069207,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2115088602","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.006851339,0.00050604437,0.9861551,0.0004372903,0.00007529852,0.00002031776,0.00032279533,0.00019959138,0.0054321946],"genre_scores_gemma":[0.6254915,0.0026938352,0.32063589,0.00035755732,0.00033893614,0.0003909064,0.0013571662,0.00041254528,0.048321627],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99949837,0.00020231472,0.000023067647,0.00011160836,0.00012837678,0.000036254976],"domain_scores_gemma":[0.9977181,0.0016909853,0.00016043635,0.00019868177,0.00016741743,0.000064328924],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011375275,0.00067049806,0.0012028344,0.00072836754,0.0004056113,0.0010884808,0.0030319775,0.0017337557,0.0046392162],"category_scores_gemma":[0.0039509106,0.00083237374,0.0010557304,0.0011912198,0.0012603435,0.0016287799,0.0011672182,0.001438986,0.0006528184],"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":[0.0000062241,0.000009016896,0.00017986234,0.000023938044,0.000017832626,0.000022378495,0.000013793659,0.91333324,0.000089328845,0.079896934,0.0009049814,0.0055025276],"study_design_scores_gemma":[0.0000018826591,0.0000014141891,0.000026756288,0.0000024028882,0.000002192799,0.000007181222,0.0000018281847,0.96876556,0.00002166255,0.030594913,0.0005719644,0.0000022497502],"about_ca_topic_score_codex":0.008022851,"about_ca_topic_score_gemma":0.0071552545,"teacher_disagreement_score":0.008022851,"about_ca_system_score_codex":0.001052582,"about_ca_system_score_gemma":0.00066309166,"threshold_uncertainty_score":0.01595229},"labels":[],"label_agreement":null},{"id":"W2156119285","doi":"10.1007/978-1-4020-6448-7_29","title":"Joint Simulation of Mine Spoil Uncertainty for Rehabilitation Decision Making","year":2008,"lang":"en","type":"book-chapter","venue":"Quantitative geology and geostatistics","topic":"Soil Geostatistics and Mapping","field":"Environmental Science","cited_by":6,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Rehabilitation; Autocorrelation; Stochastic simulation; Process (computing); Computer science; Variable (mathematics); Gaussian; Mathematical optimization; Engineering; Statistics; Mathematics","score_opus":0.03385554496903327,"score_gpt":0.2998453597414524,"score_spread":0.2659898147724191,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2156119285","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.1799285,0.00083864806,0.7941256,0.0020343722,0.00019795823,0.00009729067,0.00063074456,0.00041367326,0.021733204],"genre_scores_gemma":[0.9613879,0.00026454063,0.031343646,0.00012493775,0.00005933555,0.00014101206,0.00025024096,0.000080956655,0.0063474528],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99910116,0.00049580546,0.000031856835,0.0001257366,0.0001259215,0.00011961573],"domain_scores_gemma":[0.9886613,0.009952505,0.00041826948,0.00022042377,0.00049223524,0.00025519496],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0027867563,0.00080015603,0.0018644886,0.0006837148,0.0007527827,0.0020441075,0.0017956637,0.0030681419,0.005314726],"category_scores_gemma":[0.012332104,0.0011618071,0.0012773393,0.0010600883,0.001529784,0.0023340052,0.0016325122,0.002760446,0.00035259555],"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":[0.000017696695,0.0000054796346,0.0001289955,0.000003920797,0.0000050552158,0.000008774923,0.000008839756,0.9957569,0.000018594448,0.0032974023,0.00009687519,0.0006513651],"study_design_scores_gemma":[0.0000030825388,0.0000033304934,0.00001950872,0.0000011448168,0.0000013817518,0.0000019945423,0.000002680975,0.99773043,0.000016602755,0.0021680647,0.000049914757,0.0000018929458],"about_ca_topic_score_codex":0.031572357,"about_ca_topic_score_gemma":0.014868551,"teacher_disagreement_score":0.031572357,"about_ca_system_score_codex":0.0018393461,"about_ca_system_score_gemma":0.0018470312,"threshold_uncertainty_score":0.06277716},"labels":[],"label_agreement":null},{"id":"W2161687405","doi":"10.1007/978-94-007-4153-9_2","title":"Applications of Randomized Methods for Decomposing and Simulating from Large Covariance Matrices","year":2012,"lang":"en","type":"book-chapter","venue":"Quantitative geology and geostatistics","topic":"Soil Geostatistics and Mapping","field":"Environmental Science","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Singular value decomposition; Eigenvalues and eigenvectors; Mathematics; Singular value; Estimator; Power iteration; Applied mathematics; Covariance; Rank (graph theory); Covariance matrix; Matrix (chemical analysis); Estimation of covariance matrices; Algorithm; Statistics; Combinatorics; Iterative method","score_opus":0.025289585085258047,"score_gpt":0.3459418155976016,"score_spread":0.3206522305123436,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2161687405","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0008895309,0.00016260335,0.9980457,0.000065341905,0.00004350763,0.00003190873,0.00004933847,0.0003043311,0.0004077345],"genre_scores_gemma":[0.04189084,0.00038321593,0.9547902,0.00015344936,0.0001723283,0.00046033124,0.00028456957,0.000377802,0.0014872625],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9927464,0.00490502,0.00039056456,0.000778522,0.00095907174,0.0002204723],"domain_scores_gemma":[0.9642927,0.02946378,0.0011040154,0.0031650502,0.0016346832,0.00033982028],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.009319944,0.0019063787,0.0019331558,0.001266164,0.001183575,0.0015914403,0.0039409585,0.0021116273,0.007431678],"category_scores_gemma":[0.03590906,0.0014441608,0.002160909,0.002323514,0.0018789467,0.0028176191,0.0027156684,0.0042851917,0.0012833012],"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":[0.0002533006,0.0002343958,0.001048043,0.00023590113,0.00030911656,0.000116254705,0.00018289556,0.63904715,0.001561505,0.1994231,0.0066709444,0.15091744],"study_design_scores_gemma":[0.000075097094,0.00003473145,0.00007989585,0.000019626505,0.000023382836,0.000032487333,0.000013914251,0.9065864,0.0006707741,0.09024371,0.0021967085,0.000023265036],"about_ca_topic_score_codex":0.010244627,"about_ca_topic_score_gemma":0.013781302,"teacher_disagreement_score":0.010244627,"about_ca_system_score_codex":0.0015341728,"about_ca_system_score_gemma":0.0028352449,"threshold_uncertainty_score":0.049289167},"labels":[],"label_agreement":null},{"id":"W2189022047","doi":"10.1007/978-94-007-4153-9_33","title":"Practical Implementation of Non-linear Transforms for Modeling Geometallurgical Variables","year":2012,"lang":"en","type":"book-chapter","venue":"Quantitative geology and geostatistics","topic":"Soil Geostatistics and Mapping","field":"Environmental Science","cited_by":12,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Heteroscedasticity; Multivariate statistics; Categorical variable; Covariance; Computer science; Context (archaeology); Transformation (genetics); Process (computing); Econometrics; Data mining; Mathematics; Statistics; Machine learning; Geography","score_opus":0.05673982990366054,"score_gpt":0.3472963582517654,"score_spread":0.29055652834810486,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2189022047","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0008098942,0.000035278303,0.996617,0.000029228977,0.000020609703,0.000009424029,0.000041280244,0.0012100525,0.0012273259],"genre_scores_gemma":[0.031227235,0.00011481861,0.96372694,0.00003339806,0.00001994415,0.00007747861,0.00028073034,0.00047039456,0.004049043],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994535,0.00018217659,0.00003672683,0.000070095215,0.0002219849,0.000035521305],"domain_scores_gemma":[0.99899083,0.0005801941,0.000031273285,0.0001893702,0.00018826386,0.000020026931],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00091484596,0.00097458827,0.0005059646,0.00044170197,0.00039009872,0.0012170062,0.001440222,0.0008784144,0.01607551],"category_scores_gemma":[0.003919386,0.0004630249,0.00074250676,0.0008333792,0.00042126578,0.0011242657,0.0011160382,0.0015358976,0.007016987],"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":[0.00013986308,0.00014795721,0.0007140606,0.00027943382,0.00005601792,0.0003041681,0.00026434698,0.15337378,0.016779905,0.12875341,0.015482315,0.6837048],"study_design_scores_gemma":[0.000021287267,0.000024817939,0.00012541444,0.000016850568,0.000010392776,0.00017182583,0.000041118066,0.9362622,0.010650895,0.03765424,0.01500794,0.000013001779],"about_ca_topic_score_codex":0.0025957674,"about_ca_topic_score_gemma":0.004601934,"teacher_disagreement_score":0.01607551,"about_ca_system_score_codex":0.0003107918,"about_ca_system_score_gemma":0.00065782166,"threshold_uncertainty_score":0.053777993},"labels":[],"label_agreement":null},{"id":"W2196704854","doi":"10.1007/978-1-4020-3610-1_114","title":"A Step by Step Guide to Bi-Gaussian Disjunctive Kriging","year":2005,"lang":"en","type":"book-chapter","venue":"Quantitative geology and geostatistics","topic":"Soil Geostatistics and Mapping","field":"Environmental Science","cited_by":8,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Kriging; Hermite polynomials; Formalism (music); Gaussian; Applied mathematics; Polynomial; Mathematics; Simple (philosophy); Algorithm; Mathematical optimization; Computer science; Statistics; Pure mathematics; Mathematical analysis","score_opus":0.013772403251119121,"score_gpt":0.272194830875784,"score_spread":0.2584224276246649,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2196704854","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00022330467,0.0011378793,0.9838473,0.00014106836,0.00021055598,0.000089511814,0.0016266261,0.003926889,0.008796821],"genre_scores_gemma":[0.0020384605,0.0012160451,0.97213644,0.00019340836,0.000046463178,0.00026587996,0.0017697443,0.0016637088,0.020669851],"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99938345,0.00016319781,0.000060320173,0.00008706449,0.00027370424,0.000032278534],"domain_scores_gemma":[0.99860495,0.00064407196,0.000026845597,0.00018180386,0.0005145092,0.000027805938],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009961692,0.0016332289,0.0013938302,0.0015784702,0.0007102306,0.0015393157,0.0033595818,0.0012532192,0.061206583],"category_scores_gemma":[0.0049398486,0.0019581916,0.0012308066,0.0028887005,0.0005303331,0.0015938288,0.001350158,0.0031699152,0.04472401],"study_design_candidate":"theoretical_or_conceptual","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":[0.000040193077,0.00013217822,0.000445858,0.000989744,0.000096641044,0.00024165022,0.0002272238,0.046725523,0.0044221897,0.06173265,0.28180256,0.6031436],"study_design_scores_gemma":[0.000025644713,0.00003478171,0.000864649,0.00024951302,0.000054942648,0.00058046303,0.000093225666,0.15624982,0.005244537,0.10907587,0.72740215,0.00012444671],"about_ca_topic_score_codex":0.010455698,"about_ca_topic_score_gemma":0.030571956,"teacher_disagreement_score":0.061206583,"about_ca_system_score_codex":0.0008258208,"about_ca_system_score_gemma":0.0017346151,"threshold_uncertainty_score":0.20475638},"labels":[],"label_agreement":null},{"id":"W2221143990","doi":"10.1007/978-1-4020-3610-1_49","title":"Geostatistical Investigation of Elemental Enrichment in Hydrothermal Mineral Deposits","year":2005,"lang":"en","type":"book-chapter","venue":"Quantitative geology and geostatistics","topic":"Geochemistry and Geologic Mapping","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Hydrothermal circulation; Geology; Mineralogy; Covariance; Metal; Alunite; Anisotropy; Trace element; Chemistry; Geochemistry; Mathematics; Paleontology","score_opus":0.021519897847269893,"score_gpt":0.2559577845678341,"score_spread":0.23443788672056418,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2221143990","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.31479526,0.0022294947,0.6641985,0.0006487761,0.00007057972,0.000093722825,0.0031224682,0.003824203,0.011016988],"genre_scores_gemma":[0.6960967,0.0016241702,0.2907403,0.00013105632,0.000086416905,0.00008862497,0.0031785364,0.0004740879,0.007580203],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99974054,0.00006547273,0.000021299467,0.00003996748,0.00011520227,0.0000174466],"domain_scores_gemma":[0.9993462,0.00038761325,0.00008680465,0.00004999206,0.00011283099,0.000016556121],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00046902365,0.0003557081,0.0003132047,0.0021104328,0.00020421034,0.0007574676,0.0005767596,0.00024980563,0.0013123064],"category_scores_gemma":[0.001628476,0.00039356225,0.0004878843,0.002436568,0.0003147937,0.00044870982,0.00045111752,0.00024113207,0.0003322088],"study_design_candidate":"observational","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":[0.0003891169,0.00021556772,0.10444944,0.0007944111,0.0005409431,0.0008603102,0.00058718375,0.20398407,0.10264197,0.05378619,0.010987425,0.52076334],"study_design_scores_gemma":[0.000035843284,0.0001385054,0.12374534,0.000044626024,0.00014023152,0.0013810096,0.0005843186,0.77435535,0.047813863,0.03735609,0.014316892,0.00008792847],"about_ca_topic_score_codex":0.0054604243,"about_ca_topic_score_gemma":0.010403011,"teacher_disagreement_score":0.0054604243,"about_ca_system_score_codex":0.00039216474,"about_ca_system_score_gemma":0.0008123523,"threshold_uncertainty_score":0.010857284},"labels":[],"label_agreement":null},{"id":"W2278299854","doi":"10.1007/978-94-007-4153-9_42","title":"Interpolation of Concentration Measurements by Kriging Using Flow Coordinates","year":2012,"lang":"en","type":"book-chapter","venue":"Quantitative geology and geostatistics","topic":"Soil Geostatistics and Mapping","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Curvilinear coordinates; Kriging; Interpolation (computer graphics); Coordinate system; Cartesian coordinate system; Hydraulic head; Spatial reference system; Flow (mathematics); Plume; Orthogonal coordinates; Discretization; Stream function; Transformation (genetics); Advection; Nonlinear system; Geology; Mathematics; Computer science; Geometry; Mathematical analysis; Geotechnical engineering; Mechanics; Geography; Remote sensing; Statistics; Physics; Chemistry; Meteorology","score_opus":0.04756708123971831,"score_gpt":0.2817556148915185,"score_spread":0.2341885336518002,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2278299854","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.011284887,0.00023583352,0.9816288,0.000040323317,0.000055856563,0.000041022897,0.00051599543,0.003070635,0.0031266697],"genre_scores_gemma":[0.1178037,0.00054155366,0.87473726,0.00001629458,0.000017899647,0.00007264236,0.0011542748,0.00044964204,0.0052067596],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99961936,0.000071384326,0.000021703887,0.000106233485,0.00015452856,0.000026737564],"domain_scores_gemma":[0.99969304,0.00011398041,0.000025248391,0.00007435231,0.000087793276,0.000005576344],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005302828,0.00077014527,0.00058125093,0.001125543,0.00041974912,0.0006478229,0.00087161147,0.00036922778,0.0025308777],"category_scores_gemma":[0.0015417419,0.00060002145,0.0008517746,0.0024701545,0.000238236,0.0006661015,0.00046785708,0.00069915387,0.0016572635],"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":[0.00016448577,0.000074901756,0.0041663274,0.00038352163,0.000093026065,0.000083745304,0.0003536877,0.35457692,0.0285171,0.01324311,0.005336467,0.5930068],"study_design_scores_gemma":[0.00003035224,0.00008875127,0.0049954173,0.000051225732,0.000071299444,0.00013843022,0.00006897312,0.9004427,0.050851483,0.010972398,0.03218736,0.0001015923],"about_ca_topic_score_codex":0.021635778,"about_ca_topic_score_gemma":0.02701638,"teacher_disagreement_score":0.021635778,"about_ca_system_score_codex":0.0006659949,"about_ca_system_score_gemma":0.0010173842,"threshold_uncertainty_score":0.043019652},"labels":[],"label_agreement":null},{"id":"W2506401077","doi":"10.1007/978-1-4020-3610-1","title":"Geostatistics Banff 2004","year":2005,"lang":"en","type":"book","venue":"Quantitative geology and geostatistics","topic":"Soil Geostatistics and Mapping","field":"Environmental Science","cited_by":105,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Geostatistics; Beauty; Geography; Ideal (ethics); Physical geography; Geology; Mathematics; Statistics; Art; Aesthetics; Political science; Spatial variability","score_opus":0.015605300585507588,"score_gpt":0.2587210415367155,"score_spread":0.24311574095120791,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2506401077","genre_codex":"methods","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.000718904,0.028327696,0.613411,0.009857362,0.006147772,0.00013598101,0.005021904,0.0071226805,0.32925677],"genre_scores_gemma":[0.011816208,0.021425415,0.240145,0.0045079864,0.002694283,0.00044688222,0.006376683,0.003963037,0.7086245],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99907124,0.0001912551,0.000071620256,0.00018667098,0.00043315176,0.000046120003],"domain_scores_gemma":[0.99774605,0.0009228675,0.000074984855,0.00033119656,0.00086259603,0.00006231409],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011718158,0.0015216301,0.0014557567,0.0026358576,0.00071640784,0.0026763375,0.0010567423,0.0014644775,0.055947386],"category_scores_gemma":[0.0038788347,0.0011893627,0.0006532497,0.0036553163,0.0010725929,0.0023587716,0.001018029,0.0035168568,0.042685278],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000011971591,0.000010721722,0.00018895858,0.00016164996,0.000017972192,0.000035076508,0.00008467224,0.0020430174,0.00027722557,0.104393505,0.612124,0.28065115],"study_design_scores_gemma":[0.0000051053344,0.0000063493603,0.00040142745,0.0001121812,0.000017178329,0.00016214147,0.000033009717,0.0032119649,0.00037518845,0.079493254,0.9161677,0.000014541871],"about_ca_topic_score_codex":0.01392476,"about_ca_topic_score_gemma":0.020693546,"teacher_disagreement_score":0.9860752,"about_ca_system_score_codex":0.0017445441,"about_ca_system_score_gemma":0.002550899,"threshold_uncertainty_score":0.1871627},"labels":[],"label_agreement":null},{"id":"W2522621583","doi":"10.1007/978-3-319-46819-8_6","title":"A New High-Order, Nonstationary, and Transformation Invariant Spatial Simulation Approach","year":2017,"lang":"en","type":"book-chapter","venue":"Quantitative geology and geostatistics","topic":"Soil Geostatistics and Mapping","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Raster graphics; Computer science; Similarity (geometry); Algorithm; Data mining; Spatial analysis; Transformation (genetics); Similarity measure; Pattern recognition (psychology); Artificial intelligence; Mathematics; Image (mathematics); Statistics","score_opus":0.0257329332345454,"score_gpt":0.262575889865118,"score_spread":0.2368429566305726,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2522621583","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0018693466,0.00005686222,0.99593914,0.000053156367,0.000026910502,0.000010601063,0.000024905288,0.00014398721,0.0018750753],"genre_scores_gemma":[0.26441726,0.00054971233,0.71832865,0.00024687868,0.00024807174,0.00022839538,0.0003988463,0.000773664,0.014808536],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993044,0.00022812432,0.000038932747,0.00012105636,0.00024487707,0.000062577274],"domain_scores_gemma":[0.9982955,0.00097599794,0.0001407701,0.00021823538,0.00029003344,0.00007951274],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012262907,0.0006406967,0.0009282889,0.00084533566,0.0005808413,0.001207746,0.0019896084,0.0010044561,0.0037894822],"category_scores_gemma":[0.0040244386,0.0005571502,0.0012369439,0.00094350055,0.0008792346,0.0015987204,0.0017412961,0.001999828,0.00086089823],"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":[0.000026184973,0.00006111522,0.00048368413,0.000040910007,0.000060695158,0.0000647269,0.000058641803,0.858123,0.0017541794,0.10333303,0.0013647128,0.03462911],"study_design_scores_gemma":[0.0000010949548,0.000003223402,0.000026157772,0.0000010593818,0.000003161493,0.0000057426537,0.0000014748032,0.9930688,0.00010591625,0.0063709742,0.0004101007,0.0000023660746],"about_ca_topic_score_codex":0.006178705,"about_ca_topic_score_gemma":0.005182694,"teacher_disagreement_score":0.006178705,"about_ca_system_score_codex":0.0009659187,"about_ca_system_score_gemma":0.0014253537,"threshold_uncertainty_score":0.0126770735},"labels":[],"label_agreement":null},{"id":"W2592900105","doi":"10.1007/978-3-319-46819-8_50","title":"Statistical Scale-Up of Dispersive Transport in Heterogeneous Reservoir","year":2017,"lang":"en","type":"book-chapter","venue":"Quantitative geology and geostatistics","topic":"Groundwater flow and contamination studies","field":"Environmental Science","cited_by":4,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Random walk; Scale (ratio); Grid; Scaling; Continuous-time random walk; Statistical physics; Stochastic simulation; Mathematics; Statistics; Geometry; Physics","score_opus":0.02429169647167075,"score_gpt":0.2739103032459604,"score_spread":0.24961860677428963,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2592900105","genre_codex":"empirical","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.60018027,0.0016922579,0.38691354,0.0010297537,0.00009197738,0.000043233806,0.0005553441,0.0010260922,0.00846749],"genre_scores_gemma":[0.9872636,0.0004904049,0.00969874,0.00004743442,0.00007032585,0.000020029298,0.00023537266,0.00011083282,0.0020632024],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9998073,0.00004484118,0.000009545409,0.0000680168,0.000043103195,0.000027135191],"domain_scores_gemma":[0.9972451,0.0019285867,0.00021952836,0.00032330494,0.00017851921,0.000104929815],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00076906127,0.00033300216,0.00035771294,0.0008137418,0.00045487907,0.00087085605,0.00080492574,0.00045988028,0.00096600165],"category_scores_gemma":[0.005096568,0.00041936315,0.0005482433,0.00087297166,0.0012747445,0.0018004854,0.00081965205,0.00076389336,0.00011230732],"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":[0.00014162004,0.000076984565,0.01471282,0.00018870873,0.00014590779,0.0004643051,0.000293464,0.77560854,0.016599208,0.14848442,0.0019972266,0.04128678],"study_design_scores_gemma":[0.000004227213,0.000019452396,0.0056392103,0.000005962503,0.000014835314,0.000040834235,0.00004424675,0.9553409,0.0013947638,0.036960162,0.0005161909,0.000019255458],"about_ca_topic_score_codex":0.0048234784,"about_ca_topic_score_gemma":0.003072227,"teacher_disagreement_score":0.0048234784,"about_ca_system_score_codex":0.001017677,"about_ca_system_score_gemma":0.000405395,"threshold_uncertainty_score":0.009590805},"labels":[],"label_agreement":null},{"id":"W2593176887","doi":"10.1007/978-3-319-46819-8_19","title":"A High-Order, Data-Driven Framework for Joint Simulation of Categorical Variables","year":2017,"lang":"en","type":"book-chapter","venue":"Quantitative geology and geostatistics","topic":"Soil Geostatistics and Mapping","field":"Environmental Science","cited_by":8,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Categorical variable; Spatial analysis; Joint probability distribution; Order statistic; Computer science; Variogram; Algorithm; Geostatistics; Statistics; Spatial dependence; Data mining; Kriging; Grid; Mathematics; Spatial variability","score_opus":0.07882150043766899,"score_gpt":0.32656439669334875,"score_spread":0.24774289625567975,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2593176887","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00079410797,0.00004391446,0.99814045,0.00007109487,0.000024009365,0.000020194806,0.00007172078,0.00027619235,0.00055833295],"genre_scores_gemma":[0.1289446,0.0002816722,0.86267984,0.00031934513,0.00016741737,0.0005806909,0.00084689073,0.00053846854,0.0056411214],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9970686,0.0015630911,0.00018575287,0.00032726457,0.00065730273,0.00019801519],"domain_scores_gemma":[0.98367983,0.012959063,0.00043805025,0.0011142719,0.0014050794,0.00040369845],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0066856495,0.0010085294,0.0017704514,0.0009160963,0.0010280733,0.0027665917,0.004896968,0.002327447,0.008703408],"category_scores_gemma":[0.023280976,0.0014001296,0.002168544,0.0014970446,0.0017101306,0.0022453824,0.0031274788,0.0049966746,0.0019163087],"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":[0.000043546173,0.000039801238,0.00046798776,0.00004651399,0.00004051134,0.00007058952,0.0000888891,0.8632931,0.0003399551,0.12161521,0.0013008467,0.0126530295],"study_design_scores_gemma":[0.000005157925,0.0000038610374,0.000016459619,0.0000033148265,0.000002778724,0.0000067929736,0.0000026561818,0.97256684,0.00007175211,0.026901271,0.00041533567,0.0000037342104],"about_ca_topic_score_codex":0.014490499,"about_ca_topic_score_gemma":0.01646623,"teacher_disagreement_score":0.014490499,"about_ca_system_score_codex":0.0017430002,"about_ca_system_score_gemma":0.0034874638,"threshold_uncertainty_score":0.035357475},"labels":[],"label_agreement":null},{"id":"W2594620184","doi":"10.1007/978-3-319-46819-8_13","title":"Optimizing Infill Drilling Decisions Using Multi-armed Bandits: Application in a Long-Term, Multi-element Stockpile","year":2017,"lang":"en","type":"book-chapter","venue":"Quantitative geology and geostatistics","topic":"Reservoir Engineering and Simulation Methods","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Stockpile; Infill; Drilling; Drill; Element (criminal law); Computer science; Term (time); Point (geometry); Operations research; The Internet; Petroleum engineering; Data mining; Mathematical optimization; Engineering; Civil engineering; Mathematics; Mechanical engineering; World Wide Web; Political science","score_opus":0.08291035846930536,"score_gpt":0.3634405644992333,"score_spread":0.28053020602992795,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2594620184","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.376008,0.0027884515,0.6100718,0.0012695678,0.0001478499,0.00013738452,0.00046159382,0.0011623241,0.007953034],"genre_scores_gemma":[0.88540053,0.0005517335,0.10760186,0.00016505716,0.000057665653,0.00017199197,0.00036052626,0.0001362928,0.0055543836],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999428,0.00029513924,0.000032139254,0.000101909696,0.000060741677,0.00008203924],"domain_scores_gemma":[0.9945697,0.0045599374,0.00027565795,0.00011120033,0.0003217836,0.00016172488],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0022118746,0.001616489,0.0028411408,0.0007330397,0.0008569485,0.0019944876,0.0017451706,0.0037512751,0.0026919881],"category_scores_gemma":[0.005587686,0.0013942616,0.0010799546,0.0010904783,0.0012127529,0.0018779169,0.001656246,0.0023083647,0.0003704256],"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":[0.0000667306,0.00004305946,0.000405582,0.000022164477,0.00002583374,0.000025431578,0.000016689159,0.9923281,0.00013530221,0.00074310624,0.00020533979,0.0059826323],"study_design_scores_gemma":[0.00000647842,0.000016324206,0.00004996898,0.0000034197362,0.000005066034,0.0000023698037,0.0000057134735,0.99940324,0.00006978701,0.00038971147,0.000044905675,0.000003071428],"about_ca_topic_score_codex":0.02035179,"about_ca_topic_score_gemma":0.02036111,"teacher_disagreement_score":0.02035179,"about_ca_system_score_codex":0.0011960838,"about_ca_system_score_gemma":0.001595625,"threshold_uncertainty_score":0.040466666},"labels":[],"label_agreement":null},{"id":"W2752768744","doi":"10.1007/978-3-319-06874-9_2","title":"Probability and Statistics","year":2014,"lang":"en","type":"book-chapter","venue":"Quantitative geology and geostatistics","topic":"Probability and Statistical Research","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Natural Resources Canada; Geological Survey of Canada","funders":"","keywords":"Statistics; Poisson distribution; Mathematics; Statistical inference; Exploratory data analysis; Negative binomial distribution; Binomial distribution; Log-normal distribution; Statistical hypothesis testing; Mathematical statistics","score_opus":0.1469727245427292,"score_gpt":0.37002787814596183,"score_spread":0.22305515360323264,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2752768744","genre_codex":"other","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0009537986,0.123820595,0.14810655,0.019672468,0.009742357,0.0001131514,0.00072033063,0.0006381295,0.6962327],"genre_scores_gemma":[0.057930287,0.112268426,0.0408793,0.010709805,0.03227074,0.0006739311,0.00077970047,0.0011808862,0.74330693],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9978781,0.0007301271,0.0001061313,0.00031977438,0.00089080964,0.00007504343],"domain_scores_gemma":[0.9975948,0.0015548146,0.000117934775,0.00032490032,0.00032029758,0.000087270026],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017142092,0.0021058375,0.0020552669,0.003480117,0.0013880103,0.006211171,0.001241633,0.0024647124,0.031699225],"category_scores_gemma":[0.0074320827,0.0007005529,0.0005460102,0.0040830136,0.006337531,0.006748038,0.0021376936,0.006073888,0.018534096],"study_design_candidate":"not_applicable","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":[0.0000035498024,0.0000100059815,0.000057252346,0.00016935621,0.000009086021,0.000028233007,0.00019600285,0.00044160572,0.0000795901,0.86771196,0.090473525,0.040819783],"study_design_scores_gemma":[0.000002962156,0.0000073045653,0.00012567021,0.00013684266,0.000005302182,0.00007720057,0.00005574752,0.00071548007,0.000041142786,0.7389618,0.259863,0.0000075080225],"about_ca_topic_score_codex":0.0018777935,"about_ca_topic_score_gemma":0.0023685396,"teacher_disagreement_score":0.031699225,"about_ca_system_score_codex":0.002831913,"about_ca_system_score_gemma":0.0027265146,"threshold_uncertainty_score":0.10604441},"labels":[],"label_agreement":null},{"id":"W36299455","doi":"10.1007/978-1-4020-3610-1_39","title":"The Practice of Sequential Gaussian Simulation","year":2005,"lang":"en","type":"book-chapter","venue":"Quantitative geology and geostatistics","topic":"Soil Geostatistics and Mapping","field":"Environmental Science","cited_by":18,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Domtar (Canada)","funders":"","keywords":"Computer science; Process (computing); Context (archaeology); Simple (philosophy); Gaussian; Gaussian process; Quality (philosophy); Computer simulation; Simulation modeling; Industrial engineering; Algorithm; Mathematical optimization; Simulation; Engineering; Mathematics; Mathematical economics","score_opus":0.02347416646558786,"score_gpt":0.30343992737512004,"score_spread":0.2799657609095322,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W36299455","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00049223687,0.00022626502,0.996167,0.00029451004,0.00006453812,0.000021655345,0.000018775936,0.00017850367,0.002536542],"genre_scores_gemma":[0.09015733,0.0010124804,0.9020475,0.00045824115,0.00026838883,0.00043789024,0.00014221002,0.00033829245,0.005137729],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9848,0.0105359685,0.0005581463,0.001259899,0.0025497219,0.00029629248],"domain_scores_gemma":[0.9574122,0.030901767,0.0009493709,0.007584819,0.0027337307,0.00041821107],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0142580625,0.0011101522,0.0016963813,0.0015983857,0.0011771157,0.0033259527,0.0028946,0.002179743,0.008571584],"category_scores_gemma":[0.06421656,0.0013305683,0.0014079973,0.0028849533,0.0052735168,0.0037974452,0.003993915,0.005149588,0.003071441],"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":[0.00007147849,0.000048052094,0.0008016274,0.00015278833,0.000112969334,0.00007451338,0.00031766083,0.13037778,0.00034521372,0.7611983,0.0077609816,0.09873865],"study_design_scores_gemma":[0.000036783287,0.000018874089,0.000071925315,0.00005033057,0.000017800676,0.0000624291,0.00003163994,0.3338552,0.0004155291,0.6536428,0.01178076,0.000016046059],"about_ca_topic_score_codex":0.004787357,"about_ca_topic_score_gemma":0.004258174,"teacher_disagreement_score":0.0142580625,"about_ca_system_score_codex":0.0018193661,"about_ca_system_score_gemma":0.0032478848,"threshold_uncertainty_score":0.0754047},"labels":[],"label_agreement":null},{"id":"W37945547","doi":"10.1007/978-1-4020-3610-1_12","title":"Covariance Models with Spectral Additive Components","year":2005,"lang":"en","type":"book-chapter","venue":"Quantitative geology and geostatistics","topic":"Blind Source Separation Techniques","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Covariance; Variogram; Covariance function; Isotropy; Anisotropy; Mathematics; Applied mathematics; Fast Fourier transform; Function (biology); Algorithm; Model selection; Computer science; Mathematical optimization; Statistical physics; Statistics; Physics; Kriging; Optics","score_opus":0.03745536852320596,"score_gpt":0.2687387409482912,"score_spread":0.23128337242508523,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W37945547","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0011553838,0.0002490181,0.9965329,0.00010522552,0.00005771709,0.000008025303,0.000092425806,0.00019558893,0.0016036526],"genre_scores_gemma":[0.36489967,0.004377515,0.5410869,0.00066485576,0.00086192135,0.0005486799,0.0025116447,0.0014449644,0.08360387],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99864954,0.000573092,0.000064253836,0.00028154676,0.00033429085,0.00009728733],"domain_scores_gemma":[0.9966012,0.0021337166,0.00025984715,0.00047688856,0.00047164378,0.00005662314],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002410239,0.0018567999,0.0016324213,0.0008088872,0.00056149747,0.0021204231,0.0025870933,0.0019825925,0.0043836893],"category_scores_gemma":[0.008570044,0.0013711009,0.0020254026,0.001798143,0.001346152,0.0036773349,0.001824401,0.0027535695,0.0030688564],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000046149937,0.0000504542,0.00036897085,0.00010204224,0.000116255505,0.00006613378,0.000112597925,0.42264757,0.0008620188,0.52316886,0.0057137846,0.04674518],"study_design_scores_gemma":[0.000007349319,0.000009474369,0.000109188404,0.000014886849,0.00002847752,0.000036659334,0.000011776703,0.79135257,0.00030519845,0.20483492,0.003267822,0.000021760572],"about_ca_topic_score_codex":0.0059218323,"about_ca_topic_score_gemma":0.005256415,"teacher_disagreement_score":0.0059218323,"about_ca_system_score_codex":0.0006444689,"about_ca_system_score_gemma":0.00132212,"threshold_uncertainty_score":0.014664888},"labels":[],"label_agreement":null},{"id":"W4415543248","doi":"10.1007/978-3-031-92870-3_3","title":"Model Validation with a Set of Exhaustive 2D Multivariate, Continuous, and Categorical Examples","year":2025,"lang":"en","type":"book-chapter","venue":"Quantitative geology and geostatistics","topic":"Philosophy and History of Science","field":"Arts and Humanities","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta; Geoscience BC","funders":"","keywords":"Categorical variable; Cross-validation; Set (abstract data type); Workflow; Variogram; Model validation; Data set","score_opus":0.08623605443398083,"score_gpt":0.2760913456915237,"score_spread":0.18985529125754289,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4415543248","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.43682486,0.004164455,0.5211754,0.0018571473,0.00027022685,0.00028936486,0.018084444,0.003747014,0.013587109],"genre_scores_gemma":[0.6753442,0.0005942742,0.29313505,0.0004722575,0.00007349642,0.00037778835,0.025606887,0.00045598226,0.003940023],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9954075,0.002919646,0.00031494306,0.0005769555,0.00063458574,0.0001462709],"domain_scores_gemma":[0.95901144,0.034090612,0.00047793626,0.003724721,0.002486069,0.00020919021],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007639172,0.0015337536,0.0014704185,0.0017421641,0.0011906321,0.0017000791,0.0020698907,0.0023503208,0.0053022215],"category_scores_gemma":[0.03411425,0.00074148295,0.0024045683,0.0019187306,0.001133732,0.0014904481,0.0020377522,0.0023919176,0.0013211538],"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":[0.0009032827,0.00047867183,0.0108183045,0.0008866593,0.00044063063,0.00039864544,0.00025158265,0.842004,0.0016086493,0.007123543,0.023856826,0.11122916],"study_design_scores_gemma":[0.000093102084,0.00010721013,0.00254052,0.000079973564,0.000064764565,0.00012983775,0.000117677126,0.98300445,0.0013213377,0.009679299,0.0028228927,0.000038863538],"about_ca_topic_score_codex":0.013552559,"about_ca_topic_score_gemma":0.024872063,"teacher_disagreement_score":0.013552559,"about_ca_system_score_codex":0.00090933964,"about_ca_system_score_gemma":0.0013951734,"threshold_uncertainty_score":0.040400267},"labels":[],"label_agreement":null},{"id":"W4415543253","doi":"10.1007/978-3-031-92870-3_19","title":"Underground Stope Design Under Geological Uncertainty Using Deep Reinforcement Learning","year":2025,"lang":"en","type":"book-chapter","venue":"Quantitative geology and geostatistics","topic":"Reservoir Engineering and Simulation Methods","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Profit (economics); Variance (accounting); Set (abstract data type); Engineering design process; Conditional probability; Stage (stratigraphy)","score_opus":0.06128830584346125,"score_gpt":0.3127324252627422,"score_spread":0.25144411941928096,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4415543253","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.010159226,0.00013323697,0.98452246,0.00011140183,0.000026049702,0.000025651612,0.000057310466,0.00043848046,0.004526229],"genre_scores_gemma":[0.8451778,0.00017968573,0.14047763,0.000108032145,0.00003164246,0.00013368388,0.00018432934,0.000245561,0.013461627],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999723,0.00005771942,0.000012195051,0.000074221425,0.000081823935,0.000050985178],"domain_scores_gemma":[0.99928916,0.00035025945,0.00008825173,0.00006285017,0.00015662286,0.00005275664],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00052672677,0.0007421598,0.0010190057,0.00045468527,0.00034262546,0.00087743276,0.00096513226,0.0013264334,0.004569952],"category_scores_gemma":[0.0016371602,0.00058005215,0.000583594,0.00038461955,0.0006774566,0.0010728821,0.0013297556,0.0009723127,0.00061574264],"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":[0.000025894205,0.000009704708,0.0001646948,0.000024723746,0.000007999694,0.000029005501,0.00001348894,0.9794486,0.0007691123,0.0025148513,0.0005553596,0.01643664],"study_design_scores_gemma":[0.0000034848795,0.000014096329,0.000024617962,0.000003945859,0.0000035613682,0.0000072750017,0.0000035645928,0.9976973,0.00027204122,0.0016250381,0.00034244658,0.0000026195376],"about_ca_topic_score_codex":0.0040556896,"about_ca_topic_score_gemma":0.005334692,"teacher_disagreement_score":0.004569952,"about_ca_system_score_codex":0.00072792795,"about_ca_system_score_gemma":0.0010333001,"threshold_uncertainty_score":0.015287995},"labels":[],"label_agreement":null},{"id":"W4415543255","doi":"10.1007/978-3-031-92870-3_37","title":"Data Analysis Predicting Accelerated Melting of the Greenland Ice Sheet","year":2025,"lang":"en","type":"book-chapter","venue":"Quantitative geology and geostatistics","topic":"Cryospheric studies and observations","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Fisheries and Oceans Canada","funders":"","keywords":"Greenland ice sheet; Ice sheet; Cryosphere; Sea ice; Meltwater","score_opus":0.07571536156138876,"score_gpt":0.29057694739122025,"score_spread":0.2148615858298315,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4415543255","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96787107,0.00041042798,0.02609883,0.0003643768,0.000025456542,0.000041177682,0.0016272808,0.00032891778,0.003232479],"genre_scores_gemma":[0.9762005,0.00017653186,0.018493712,0.000041996904,0.00001109118,0.000030446736,0.0024055624,0.0000733456,0.0025668473],"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","domain_scores_codex":[0.9997652,0.000089436064,0.0000138949235,0.000051996194,0.00003993745,0.000039503233],"domain_scores_gemma":[0.9978537,0.0016982836,0.000106863714,0.00006934986,0.00023090048,0.0000409138],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0017607228,0.0006061147,0.00038146312,0.0010513569,0.00027011425,0.0008196532,0.0004660546,0.00038033986,0.00121292],"category_scores_gemma":[0.0041632443,0.00027266677,0.0005882767,0.0010629907,0.00035009018,0.00050963525,0.00039840426,0.0004581517,0.0002408111],"study_design_candidate":"observational","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":[0.00020993815,0.00004902591,0.047259912,0.000037573343,0.00007339027,0.000107024855,0.00005556063,0.89598656,0.0017069926,0.0017765336,0.001959628,0.050777752],"study_design_scores_gemma":[0.000005610617,0.000023766353,0.012034943,0.0000058185383,0.000010786679,0.000010694807,0.00003516126,0.98568964,0.00096136914,0.0009172927,0.00030124089,0.0000036888819],"about_ca_topic_score_codex":0.07732186,"about_ca_topic_score_gemma":0.07169287,"teacher_disagreement_score":0.07732186,"about_ca_system_score_codex":0.0020219907,"about_ca_system_score_gemma":0.0014390581,"threshold_uncertainty_score":0.15374357},"labels":[],"label_agreement":null},{"id":"W4415543264","doi":"10.1007/978-3-031-92870-3_33","title":"Mineral Resource Disclosure with Probabilistic Models","year":2025,"lang":"en","type":"book-chapter","venue":"Quantitative geology and geostatistics","topic":"Mining Techniques and Economics","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Probabilistic logic; Resource (disambiguation); Asset (computer security); Workflow; Audit; Statistical model; Probabilistic relevance model; Probabilistic argumentation; Sampling (signal processing)","score_opus":0.017811174486703243,"score_gpt":0.2186596471227204,"score_spread":0.20084847263601716,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4415543264","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.018515866,0.0020597219,0.85050815,0.008984033,0.0005167561,0.00007286841,0.0005551234,0.0005152572,0.11827218],"genre_scores_gemma":[0.8152763,0.0034290233,0.066209875,0.001250139,0.0011518544,0.00022885142,0.00048609622,0.0002744862,0.11169334],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9962709,0.00180826,0.00016193061,0.00046829015,0.0010306112,0.00026001583],"domain_scores_gemma":[0.9821492,0.013982388,0.0011080982,0.001944174,0.00062191556,0.00019424327],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0048633562,0.00086834293,0.0011328695,0.00085580815,0.00089504576,0.0043434873,0.0019042168,0.0029390194,0.013077436],"category_scores_gemma":[0.03078411,0.0009856104,0.0013930843,0.0013802404,0.0025703558,0.00804375,0.0025574628,0.0038437666,0.0018414651],"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":[0.000031155214,0.000027142743,0.00034191262,0.000039484854,0.000021450536,0.00006631806,0.00008258818,0.08432818,0.000058167305,0.8917454,0.005958906,0.017299319],"study_design_scores_gemma":[0.000005045967,0.000006078402,0.00006981837,0.0000117447635,0.000007654185,0.00004595902,0.000018201265,0.148668,0.0000522723,0.84796345,0.0031432717,0.000008515155],"about_ca_topic_score_codex":0.00252538,"about_ca_topic_score_gemma":0.0019475354,"teacher_disagreement_score":0.013077436,"about_ca_system_score_codex":0.0018975178,"about_ca_system_score_gemma":0.00123615,"threshold_uncertainty_score":0.04374838},"labels":[],"label_agreement":null},{"id":"W4415543281","doi":"10.1007/978-3-031-92870-3_22","title":"Application of Generative Adversarial Networks (GAN) to Geostatistical Modeling of Categorical Variables","year":2025,"lang":"en","type":"book-chapter","venue":"Quantitative geology and geostatistics","topic":"Soil Geostatistics and Mapping","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Discriminator; Categorical variable; Generator (circuit theory); Process (computing); Convolutional neural network; Artificial neural network; Generative grammar; Adversarial system; Kriging","score_opus":0.015980153223701492,"score_gpt":0.25899533097434657,"score_spread":0.24301517775064507,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4415543281","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0030995707,0.00035597754,0.9941346,0.000318357,0.000056217523,0.000013898487,0.00009741422,0.0004616592,0.0014623647],"genre_scores_gemma":[0.49669516,0.0016297658,0.48482484,0.00089500955,0.00048208758,0.00021922593,0.0012308588,0.00062730414,0.013395767],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99924624,0.0004217745,0.000025751608,0.00013475158,0.00012513479,0.000046440815],"domain_scores_gemma":[0.9964413,0.0029168387,0.000111002344,0.00023385626,0.00023216143,0.00006492993],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0019148827,0.0008458235,0.00085178594,0.00059862423,0.0002342495,0.00077032513,0.0015476503,0.00097648334,0.0021045913],"category_scores_gemma":[0.004685675,0.00054672605,0.0010570709,0.00089441455,0.0007811472,0.0007818171,0.0016407188,0.002256579,0.0006100008],"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":[0.000019856545,0.000015502952,0.0003505634,0.000034433102,0.00005137906,0.000030508105,0.000038822396,0.93266445,0.0004476336,0.022861367,0.00256991,0.04091563],"study_design_scores_gemma":[8.1377544e-7,0.0000029994783,0.00003376538,0.0000030311733,0.0000021348742,0.000007931974,0.0000016109927,0.989011,0.00008294064,0.0105417,0.00031022038,0.00000191801],"about_ca_topic_score_codex":0.008592737,"about_ca_topic_score_gemma":0.009835924,"teacher_disagreement_score":0.008592737,"about_ca_system_score_codex":0.00094851374,"about_ca_system_score_gemma":0.00067501666,"threshold_uncertainty_score":0.017085433},"labels":[],"label_agreement":null},{"id":"W4415543900","doi":"10.1007/978-3-031-92870-3_18","title":"Development of a Transfer-Learning Core-Image Based Classification Approach Across Diverse Geological Settings","year":2025,"lang":"en","type":"book-chapter","venue":"Quantitative geology and geostatistics","topic":"Domain Adaptation and Few-Shot Learning","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Transfer of learning; Transferability; Intuition; Concatenation (mathematics); Knowledge base; Feature (linguistics); Benchmarking","score_opus":0.07022650790540554,"score_gpt":0.3132626863127834,"score_spread":0.2430361784073779,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4415543900","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0070406185,0.00013677435,0.9870816,0.00015152816,0.00004901585,0.0001286583,0.00022467913,0.0026787308,0.0025085765],"genre_scores_gemma":[0.10589868,0.00022383338,0.8829525,0.00035315802,0.000071542745,0.00026029066,0.0019699847,0.00036603567,0.00790394],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9991166,0.00015491243,0.000047265676,0.00034079113,0.0002474316,0.000092974195],"domain_scores_gemma":[0.9987117,0.00027149863,0.00004239588,0.0002792602,0.00061973487,0.000075439915],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018831374,0.0009872909,0.0010901776,0.001500875,0.00076786877,0.0012765683,0.0033657728,0.0015883627,0.003619016],"category_scores_gemma":[0.0028313852,0.00046446646,0.0013560388,0.0018153872,0.0006476232,0.0021458247,0.003372305,0.0026434073,0.0031705918],"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":[0.00006208361,0.00031071127,0.0013889502,0.000105036765,0.00010133252,0.00009874755,0.00018173369,0.056541536,0.015035509,0.007543253,0.012029881,0.90660125],"study_design_scores_gemma":[0.000008337714,0.000058550384,0.00080869254,0.000019098361,0.000027353331,0.00010805069,0.000110166875,0.97067237,0.008279993,0.0137047265,0.006188156,0.000014504238],"about_ca_topic_score_codex":0.010135563,"about_ca_topic_score_gemma":0.014729852,"teacher_disagreement_score":0.010135563,"about_ca_system_score_codex":0.0008405341,"about_ca_system_score_gemma":0.0014210518,"threshold_uncertainty_score":0.020153105},"labels":[],"label_agreement":null},{"id":"W4415543907","doi":"10.1007/978-3-031-92870-3_4","title":"High-Order Stochastic Simulation via Semidefinite Programming","year":2025,"lang":"en","type":"book-chapter","venue":"Quantitative geology and geostatistics","topic":"Soil Geostatistics and Mapping","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Center for Diagnosis and Research on Alzheimer's Disease","funders":"","keywords":"Probability distribution; Stochastic simulation; Context (archaeology); Polynomial; Gaussian; Field (mathematics); Distribution (mathematics); Conditional probability distribution; Spatial analysis; Stochastic process","score_opus":0.017759431385342285,"score_gpt":0.26796926339081295,"score_spread":0.25020983200547064,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4415543907","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0036337406,0.000114070615,0.9878819,0.00022041665,0.000032088556,0.000020699032,0.00010347393,0.0003032889,0.007690297],"genre_scores_gemma":[0.525905,0.0006289688,0.44139427,0.00048235638,0.0001703157,0.0005505172,0.0008541735,0.0012452746,0.028769104],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9986921,0.00069599925,0.000042290423,0.00015269154,0.00031577563,0.00010121964],"domain_scores_gemma":[0.9919367,0.0067327064,0.00028160686,0.00033313836,0.00048596642,0.00022995043],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0023039728,0.0013045955,0.0013693,0.00047613314,0.0004698412,0.0021558695,0.0013288745,0.0012430304,0.008918082],"category_scores_gemma":[0.008542113,0.0008224154,0.0009973847,0.0007075425,0.0017415116,0.0015444064,0.0020315633,0.0030318305,0.0014167251],"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":[0.000029691877,0.00004224794,0.00015499778,0.000049067672,0.000022633887,0.00003560963,0.000035766527,0.8654574,0.00032989026,0.1234455,0.0022618955,0.008135268],"study_design_scores_gemma":[0.0000033741967,0.000004168918,0.000008823512,0.00000272152,9.968668e-7,0.0000033164247,0.000002039444,0.97226024,0.00006448734,0.027405335,0.00024264363,0.0000019568529],"about_ca_topic_score_codex":0.0029531184,"about_ca_topic_score_gemma":0.0038695473,"teacher_disagreement_score":0.008918082,"about_ca_system_score_codex":0.0012194982,"about_ca_system_score_gemma":0.0015746078,"threshold_uncertainty_score":0.029833913},"labels":[],"label_agreement":null},{"id":"W98666003","doi":"10.1007/978-1-4020-3610-1_1","title":"Accounting for Geological Boundaries in Geostatical Modeling of Multiple Rock Types","year":2005,"lang":"en","type":"book-chapter","venue":"Quantitative geology and geostatistics","topic":"Soil Geostatistics and Mapping","field":"Environmental Science","cited_by":14,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Covariance; Boundary (topology); Geology; Identification (biology); Variance (accounting); Domain (mathematical analysis); Computer science; Algorithm; Accounting; Statistics; Mathematics","score_opus":0.03529075227571926,"score_gpt":0.2777996117847244,"score_spread":0.24250885950900514,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W98666003","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.013613208,0.0011237449,0.9781883,0.0004281895,0.00010377762,0.00001572679,0.000092075345,0.0003433398,0.006091598],"genre_scores_gemma":[0.37001967,0.0019381501,0.6133918,0.00020583879,0.00017106913,0.00016274642,0.00029496284,0.0005093318,0.013306436],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99951017,0.00019930588,0.00003164745,0.00007011912,0.00015745327,0.00003127773],"domain_scores_gemma":[0.9979012,0.0015973642,0.00010620909,0.00019124785,0.00015043761,0.000053457516],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013589393,0.0006228817,0.0008632306,0.00050474616,0.000766543,0.001668157,0.0017858001,0.0015773509,0.0022437368],"category_scores_gemma":[0.005997384,0.001004502,0.0010797061,0.0012486647,0.0011686711,0.0036214686,0.0016257508,0.0022485435,0.00051944173],"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":[0.0000067932388,0.000011055482,0.00052838004,0.000024759007,0.000016893742,0.00004924865,0.000105699946,0.9146061,0.00026624484,0.06085241,0.0013318153,0.022200592],"study_design_scores_gemma":[0.0000020488467,0.0000041370045,0.000108308406,0.000011980699,0.000008065976,0.000022415808,0.000021539443,0.91995066,0.00025862013,0.076400995,0.0032042086,0.000007027885],"about_ca_topic_score_codex":0.015666295,"about_ca_topic_score_gemma":0.022282658,"teacher_disagreement_score":0.015666295,"about_ca_system_score_codex":0.00083035557,"about_ca_system_score_gemma":0.001443828,"threshold_uncertainty_score":0.031150222},"labels":[],"label_agreement":null}]}