{"meta":{"query_hash":"35835a535c4f","filters":{"venue":"International Journal of Mining and Mineral Engineering"},"cohort_total":22,"direct_labels_cover":0,"predictions_cover":22,"exported":22,"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/35835a535c4f","api":"https://metacan.xera.ac/api/v1/cohort?venue=International+Journal+of+Mining+and+Mineral+Engineering"},"results":[{"id":"W2004365119","doi":"10.1504/ijmme.2015.067951","title":"Jet grouting: using artificial neural networks to predict soilcrete column diameter - part II","year":2015,"lang":"en","type":"article","venue":"International Journal of Mining and Mineral Engineering","topic":"Grouting, Rheology, and Soil Mechanics","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Artificial neural network; Range (aeronautics); Jet (fluid); Column (typography); Grout; Field (mathematics); Data mining; Engineering; Artificial intelligence; Computer science; Machine learning; Geotechnical engineering; Mathematics; Structural engineering","score_opus":0.028094438480138716,"score_gpt":0.23706311977736091,"score_spread":0.2089686812972222,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2004365119","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":[0.85585743,0.0005411772,0.13996089,0.00016616767,0.000064466985,0.000085480664,0.0001934503,0.0005535614,0.0025774355],"genre_scores_gemma":[0.9717119,0.00024254009,0.026060909,0.000023851093,0.000016320488,0.000047117064,0.00021610361,0.000016617118,0.0016645753],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9999093,0.000016903763,0.000007061868,0.000023866993,0.000029924267,0.00001300794],"domain_scores_gemma":[0.99975437,0.00013468246,0.000030453524,0.0000130354165,0.000057564557,0.000009823221],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00033959548,0.0005381787,0.00029419182,0.0004967206,0.0001720929,0.00057164714,0.00041250544,0.0005589555,0.0006272754],"category_scores_gemma":[0.00080019067,0.00022040622,0.0002940205,0.00046407589,0.00017087653,0.00054454565,0.00022281603,0.00034715794,0.00014977097],"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":[0.00024468024,0.00022379411,0.01453904,0.000058273832,0.000049890856,0.00009783817,0.00003149687,0.84213364,0.01022295,0.00028569272,0.00045465995,0.13165802],"study_design_scores_gemma":[0.0000022976194,0.000039716517,0.0019784945,0.0000024489984,0.00000434007,0.000004314903,0.0000064180194,0.9962942,0.001515076,0.00008309017,0.000065627944,0.0000039952292],"about_ca_topic_score_codex":0.010194966,"about_ca_topic_score_gemma":0.008047152,"teacher_disagreement_score":0.010194966,"about_ca_system_score_codex":0.00038587447,"about_ca_system_score_gemma":0.0002531728,"threshold_uncertainty_score":0.020271242},"labels":[],"label_agreement":null},{"id":"W2017275588","doi":"10.1504/ijmme.2009.029320","title":"GenRel: A computerised model for reliability prediction of mining machinery","year":2009,"lang":"en","type":"article","venue":"International Journal of Mining and Mineral Engineering","topic":"Mineral Processing and Grinding","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Laurentian University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Reliability (semiconductor); Reliability engineering; Computer science; Engineering; Data mining","score_opus":0.013036145474947504,"score_gpt":0.23397357184124562,"score_spread":0.22093742636629812,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2017275588","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":[0.056960538,0.0003631362,0.93577206,0.0006622944,0.00009598029,0.00010495791,0.0012313493,0.001194449,0.0036151994],"genre_scores_gemma":[0.7807668,0.0005446548,0.20924272,0.00027431874,0.00013243697,0.0005003503,0.0017011685,0.00019708226,0.006640587],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99954957,0.00019075889,0.0000221503,0.00010611075,0.00009285105,0.00003858405],"domain_scores_gemma":[0.9973967,0.0019107198,0.00023709195,0.00013449216,0.00025304392,0.00006797334],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001633205,0.0005943301,0.0008159159,0.0007339606,0.0003423773,0.0009859477,0.0021205675,0.0013959045,0.0030791438],"category_scores_gemma":[0.0068279114,0.0005395856,0.00084989815,0.0006870064,0.0006132629,0.0010789642,0.00067953876,0.0013210148,0.00056938286],"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":[0.000022986422,0.00001709968,0.000648543,0.000015307383,0.000014317829,0.000024193583,0.000013119109,0.9906088,0.0001363471,0.0032304553,0.0005041071,0.004764731],"study_design_scores_gemma":[0.0000028694658,0.0000055118994,0.00007003626,0.0000012489313,0.0000017954809,0.000005481333,8.274708e-7,0.99797875,0.000024437655,0.0017407122,0.00016655713,0.0000019025068],"about_ca_topic_score_codex":0.013794976,"about_ca_topic_score_gemma":0.008590565,"teacher_disagreement_score":0.013794976,"about_ca_system_score_codex":0.0013664087,"about_ca_system_score_gemma":0.00094732834,"threshold_uncertainty_score":0.027429402},"labels":[],"label_agreement":null},{"id":"W2040084934","doi":"10.1504/ijmme.2014.066577","title":"A multi-step approach to long-term open-pit production planning","year":2014,"lang":"en","type":"article","venue":"International Journal of Mining and Mineral Engineering","topic":"Mining Techniques and Economics","field":"Engineering","cited_by":28,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Canadian Natural Resources; University of Alberta","funders":"","keywords":"Integer programming; Scheduling (production processes); Mathematical optimization; Heuristic; Cluster analysis; Production planning; Computer science; Open-pit mining; Linear programming; Key (lock); Term (time); Hierarchical clustering; Production (economics); Engineering; Algorithm; Mathematics; Machine learning","score_opus":0.027189726139452846,"score_gpt":0.2628570186568205,"score_spread":0.23566729251736765,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2040084934","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":[0.004383293,0.00006668039,0.9928797,0.000052406867,0.00001046603,0.00010693396,0.00003857244,0.00006944801,0.0023925123],"genre_scores_gemma":[0.23824997,0.00019394874,0.75680876,0.000051642204,0.000016740958,0.00058115553,0.00014259483,0.00007766444,0.0038774493],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99914587,0.00032061452,0.00004298895,0.00014405217,0.0002591233,0.00008722103],"domain_scores_gemma":[0.99885345,0.000675584,0.00013739028,0.000086154,0.00019293137,0.000054501998],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0018415906,0.0008458984,0.00078293984,0.0007319894,0.0005567937,0.001218372,0.0022191468,0.00096199755,0.0057402365],"category_scores_gemma":[0.0021817381,0.0008846144,0.0012142325,0.0008291794,0.00070270896,0.0010602085,0.0014517945,0.0014023348,0.0005553846],"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":[0.000019249206,0.000030048508,0.00016333156,0.000090762514,0.000020016449,0.000053249325,0.00005308732,0.97431767,0.0012942653,0.007803275,0.00018412119,0.015970968],"study_design_scores_gemma":[0.0000085557285,0.00008784014,0.000105807514,0.000017512826,0.00001021898,0.000021505288,0.000027458109,0.99102235,0.0010018692,0.006067083,0.0016200063,0.000009718406],"about_ca_topic_score_codex":0.0039029764,"about_ca_topic_score_gemma":0.006753339,"teacher_disagreement_score":0.0057402365,"about_ca_system_score_codex":0.001229386,"about_ca_system_score_gemma":0.0023754134,"threshold_uncertainty_score":0.019202948},"labels":[],"label_agreement":null},{"id":"W2057974480","doi":"10.1504/ijmme.2010.035314","title":"Hierarchical mine production scheduling using discrete-event simulation","year":2010,"lang":"en","type":"article","venue":"International Journal of Mining and Mineral Engineering","topic":"Mining Techniques and Economics","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Canadian Natural Resources; University of Alberta","funders":"","keywords":"Discrete event simulation; Scheduling (production processes); Simulation modeling; Open-pit mining; Computer science; Time horizon; Production planning; Engineering; Production (economics); Crusher; Mining engineering; Simulation; Mathematical optimization; Operations management","score_opus":0.012867048899603372,"score_gpt":0.2609300909512013,"score_spread":0.2480630420515979,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2057974480","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":[0.086051956,0.00010170685,0.9066932,0.00018664359,0.00003610664,0.00018528015,0.00039234394,0.0011664745,0.005186206],"genre_scores_gemma":[0.9036563,0.000113305934,0.09433494,0.000029837862,0.00001070456,0.00021959691,0.000341353,0.000047371657,0.0012465894],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9992786,0.00031589932,0.00005592159,0.000094714145,0.0001828604,0.00007202874],"domain_scores_gemma":[0.9980566,0.0012958344,0.00018315167,0.00017405399,0.00020152201,0.000088815286],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0010976571,0.00056040596,0.00081347744,0.00044715448,0.0004555236,0.0011012764,0.0011196316,0.0007480148,0.0018893623],"category_scores_gemma":[0.0025801996,0.00050397724,0.00089150004,0.00046527226,0.0005207217,0.0007740592,0.0007296834,0.0007817381,0.00023208927],"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":[0.000009010884,0.000008438626,0.00017384355,0.0000056191607,0.0000061811475,0.000010804527,0.000007802265,0.99782,0.00016410541,0.0009632427,0.000024889723,0.0008060238],"study_design_scores_gemma":[0.0000054353827,0.0000049353325,0.00003507689,9.447837e-7,0.0000013775184,0.0000018561619,0.0000020767418,0.9992059,0.00011597722,0.0005212297,0.000103660546,0.000001604993],"about_ca_topic_score_codex":0.017124511,"about_ca_topic_score_gemma":0.0103942575,"teacher_disagreement_score":0.017124511,"about_ca_system_score_codex":0.0013965665,"about_ca_system_score_gemma":0.0017454022,"threshold_uncertainty_score":0.03404963},"labels":[],"label_agreement":null},{"id":"W2070417657","doi":"10.1504/ijmme.2011.041449","title":"Thermal characterisation of a lightweight mortar containing expanded perlite for underground insulation","year":2011,"lang":"en","type":"article","venue":"International Journal of Mining and Mineral Engineering","topic":"Innovative concrete reinforcement materials","field":"Engineering","cited_by":20,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Canadian Natural Resources","funders":"","keywords":"Perlite; Shotcrete; Mortar; Materials science; Thermal diffusivity; Thermal conductivity; Thermal insulation; Composite material; Geotechnical engineering; Geology","score_opus":0.023506426962707744,"score_gpt":0.22824302175052444,"score_spread":0.2047365947878167,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2070417657","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":[0.99770004,0.00022184919,0.001675254,0.0000049153255,0.0000036308581,0.0000064299693,0.000045671928,0.000013537753,0.00032864598],"genre_scores_gemma":[0.99755645,0.00012361011,0.0014636555,0.0000054124343,0.000001914401,0.0000052292085,0.000079532416,0.000010976253,0.00075318635],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.9998385,0.000017951194,0.000009916766,0.000028200362,0.00008524686,0.000020197278],"domain_scores_gemma":[0.9998091,0.000041303283,0.00004589326,0.000018720468,0.00006116561,0.000023833169],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001788923,0.00020470745,0.00024857657,0.00045415224,0.00017963156,0.00027092797,0.00019633965,0.0002679494,0.0006039666],"category_scores_gemma":[0.00029659126,0.00013395617,0.00016604702,0.00021002522,0.0002161212,0.00021063087,0.000115130046,0.00016672224,0.00019410392],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000068993024,0.000009905851,0.0007453791,0.00003698425,0.0000036059027,0.000062886415,0.00003422664,0.00018008852,0.9974262,0.000022269976,0.000008267244,0.0014013074],"study_design_scores_gemma":[0.0000048808747,0.00071547437,0.019751525,0.0000150332335,0.000032140008,0.00034831048,0.00014458224,0.0013579745,0.97626364,0.0000225194,0.00133417,0.000009752728],"about_ca_topic_score_codex":0.00041737108,"about_ca_topic_score_gemma":0.0019155017,"teacher_disagreement_score":0.0006039666,"about_ca_system_score_codex":0.00011181355,"about_ca_system_score_gemma":0.000097144664,"threshold_uncertainty_score":0.0020204782},"labels":[],"label_agreement":null},{"id":"W2070814474","doi":"10.1504/ijmme.2013.053167","title":"Operating risk assessment for underground metal mining systems: overview and discussion","year":2013,"lang":"en","type":"article","venue":"International Journal of Mining and Mineral Engineering","topic":"Risk and Safety Analysis","field":"Decision Sciences","cited_by":8,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Laurentian University","funders":"","keywords":"Engineering; Underground mining (soft rock); Mining engineering; Risk analysis (engineering); Construction engineering; Computer science; Forensic engineering; Business; Waste management","score_opus":0.04834443355399234,"score_gpt":0.3577756731152886,"score_spread":0.30943123956129626,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2070814474","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":[0.022634737,0.45585406,0.48422304,0.005671613,0.00064689154,0.0001471841,0.0002809098,0.0002992573,0.030242303],"genre_scores_gemma":[0.3103462,0.55240935,0.1212722,0.0010880327,0.00259847,0.00025579784,0.0005295333,0.00014678507,0.011353694],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.99865294,0.00042851604,0.000120489465,0.00013508652,0.0005745852,0.00008843017],"domain_scores_gemma":[0.99780124,0.0015381651,0.00022481913,0.000056114804,0.00034472626,0.00003495527],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0022063565,0.0012559987,0.0010478616,0.0027984043,0.00055446743,0.002207581,0.0013918291,0.0021543833,0.0022493417],"category_scores_gemma":[0.002691348,0.00043593487,0.0012391496,0.0024956665,0.00094366964,0.002601371,0.0012499326,0.0016789808,0.00061821],"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":[0.00011603368,0.00018957889,0.0043752855,0.007078755,0.00030812042,0.0010303222,0.0008996581,0.33605286,0.0048074336,0.25889167,0.012840319,0.3734099],"study_design_scores_gemma":[0.000019959256,0.0008606412,0.0077479873,0.005187337,0.00028560706,0.003674609,0.001438839,0.26158395,0.005110347,0.3826158,0.331166,0.0003089212],"about_ca_topic_score_codex":0.0015722016,"about_ca_topic_score_gemma":0.0011289142,"teacher_disagreement_score":0.0027984043,"about_ca_system_score_codex":0.0011961762,"about_ca_system_score_gemma":0.0009622285,"threshold_uncertainty_score":0.011668444},"labels":[],"label_agreement":null},{"id":"W2072131738","doi":"10.1504/ijmme.2015.067950","title":"Jet grouting: mathematical model to predict soilcrete column diameter - part I","year":2015,"lang":"en","type":"article","venue":"International Journal of Mining and Mineral Engineering","topic":"Grouting, Rheology, and Soil Mechanics","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Jet (fluid); Range (aeronautics); Stability (learning theory); Mathematical model; Column (typography); Experimental data; Mathematics; Geotechnical engineering; Mechanics; Engineering; Computer science; Structural engineering; Statistics; Physics; Aerospace engineering","score_opus":0.026012726467130085,"score_gpt":0.23625885746999747,"score_spread":0.21024613100286738,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2072131738","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":[0.055353742,0.0027816494,0.9185088,0.0006072468,0.00023555498,0.0002443908,0.0009348692,0.0011350312,0.020198686],"genre_scores_gemma":[0.89699477,0.004803355,0.06553513,0.00022479842,0.00016369787,0.0009887452,0.0010638394,0.00024306063,0.029982558],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9996793,0.000039110528,0.000023760635,0.000103579,0.00011229527,0.00004206252],"domain_scores_gemma":[0.99948335,0.00023510166,0.000090120615,0.000023630886,0.00015374777,0.000014100746],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00044364942,0.0009344946,0.00075522746,0.001101831,0.00049904746,0.0013531548,0.0015782613,0.0020164626,0.003150858],"category_scores_gemma":[0.0013213565,0.0005843059,0.0011424512,0.0010150219,0.0005725512,0.0015003484,0.00063605845,0.0010380964,0.0011269565],"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":[0.00001911767,0.000040085375,0.0014631756,0.00015290352,0.000012973306,0.00013582852,0.00006885345,0.9790177,0.0035161674,0.0038604417,0.00078039157,0.010932427],"study_design_scores_gemma":[0.0000024112337,0.000018427558,0.0002556668,0.000010076363,0.0000063058005,0.000027845777,0.000008348215,0.9976163,0.0006013418,0.00067171326,0.00077364175,0.00000794621],"about_ca_topic_score_codex":0.010349689,"about_ca_topic_score_gemma":0.0052017625,"teacher_disagreement_score":0.010349689,"about_ca_system_score_codex":0.0009565796,"about_ca_system_score_gemma":0.0010939696,"threshold_uncertainty_score":0.02057892},"labels":[],"label_agreement":null},{"id":"W2091846780","doi":"10.1504/ijmme.2008.020475","title":"Multivariate statistical analysis of gold cyanidation plant data","year":2008,"lang":"en","type":"article","venue":"International Journal of Mining and Mineral Engineering","topic":"Fault Detection and Control Systems","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université Laval","funders":"Conselho Nacional de Desenvolvimento Científico e Tecnológico","keywords":"Gold cyanidation; Principal component analysis; Multivariate statistics; Partial least squares regression; Leaching (pedology); Statistics; Latent variable; Environmental science; Data mining; Mathematics; Engineering; Computer science; Soil science; Metallurgy; Materials science; Cyanide","score_opus":0.02080420471715188,"score_gpt":0.24883874779418627,"score_spread":0.22803454307703439,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2091846780","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":[0.95009434,0.000055460743,0.045947812,0.00008504625,0.0000141005985,0.00008537464,0.0023857,0.00050377403,0.0008284913],"genre_scores_gemma":[0.9862868,0.000034792043,0.011404381,0.0000059281633,0.000007687213,0.00006874519,0.0018715236,0.000020673691,0.00029951215],"study_design_codex":"design_other","study_design_gemma":"observational","domain_scores_codex":[0.9991535,0.00015890501,0.00006127012,0.00019007018,0.00035370988,0.000082586615],"domain_scores_gemma":[0.9983815,0.00067809847,0.000223168,0.00019409115,0.00046571414,0.000057456462],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00090170663,0.00047662336,0.0005054199,0.0011976167,0.00024396284,0.00037932364,0.00028516946,0.0002515988,0.0006776658],"category_scores_gemma":[0.0028746212,0.000105726474,0.00034470495,0.0016350821,0.0002444728,0.00020222351,0.00033313644,0.00047655537,0.00015148675],"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":[0.001558779,0.00095642096,0.23702991,0.00038955486,0.00038667818,0.0016219298,0.001040558,0.1960826,0.11983346,0.0020141746,0.0033903343,0.43569562],"study_design_scores_gemma":[0.000031077358,0.00056924624,0.5724037,0.000015424941,0.00005762574,0.00035023785,0.0003972488,0.39698413,0.025615752,0.00094896357,0.0025278272,0.00009876279],"about_ca_topic_score_codex":0.0041646776,"about_ca_topic_score_gemma":0.0026469561,"teacher_disagreement_score":0.0041646776,"about_ca_system_score_codex":0.00031195785,"about_ca_system_score_gemma":0.0003764173,"threshold_uncertainty_score":0.008280873},"labels":[],"label_agreement":null},{"id":"W2098911400","doi":"10.1504/ijmme.2009.029318","title":"Laboratory investigation into rock fracturing with expansive cement","year":2009,"lang":"en","type":"article","venue":"International Journal of Mining and Mineral Engineering","topic":"Rock Mechanics and Modeling","field":"Engineering","cited_by":22,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Expansive; Cement; Geotechnical engineering; Expansive clay; Norite; Geology; Materials science; Composite material; Igneous rock; Compressive strength; Geochemistry","score_opus":0.005338260285345112,"score_gpt":0.1973636716566048,"score_spread":0.19202541137125967,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2098911400","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":[0.9976586,0.0001489042,0.001543886,0.000021604332,0.0000069486127,0.00002573007,0.00009382542,0.000038617603,0.00046187494],"genre_scores_gemma":[0.99645567,0.00023897205,0.00208632,0.00001396656,0.000007900067,0.00002958842,0.00013708844,0.000007206523,0.0010232816],"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","domain_scores_codex":[0.99973553,0.00003471365,0.000016812006,0.00004384355,0.00011964375,0.000049426526],"domain_scores_gemma":[0.9993278,0.00025351523,0.0001494582,0.00009160608,0.000120530654,0.00005704302],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00028328315,0.00039839023,0.00024113689,0.00028893488,0.00026665197,0.00018027089,0.00038705784,0.00040183845,0.0011697242],"category_scores_gemma":[0.000519543,0.00015991207,0.000316205,0.00014831485,0.00032443216,0.00024384145,0.00020495823,0.00044681577,0.0002181734],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00017416166,0.00036162374,0.0014062674,0.00006516056,0.000009634557,0.0001809289,0.00009184162,0.000523084,0.99529856,0.000047988226,0.000045898323,0.0017949292],"study_design_scores_gemma":[0.000022631737,0.008065797,0.0039278534,0.0000059647473,0.000025979876,0.00021387234,0.00010809196,0.0016671945,0.98540026,0.000045101224,0.000507504,0.000009703129],"about_ca_topic_score_codex":0.00067822664,"about_ca_topic_score_gemma":0.00089262414,"teacher_disagreement_score":0.0011697242,"about_ca_system_score_codex":0.00014937477,"about_ca_system_score_gemma":0.00019535238,"threshold_uncertainty_score":0.003913045},"labels":[],"label_agreement":null},{"id":"W2141292481","doi":"10.1504/ijmme.2012.047998","title":"Mixed-Integer Linear Programming formulation for block-cave sequence optimisation","year":2012,"lang":"en","type":"article","venue":"International Journal of Mining and Mineral Engineering","topic":"Mining Techniques and Economics","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Okanagan University College; University of British Columbia, Okanagan Campus; University of British Columbia; Canadian Natural Resources; University of Alberta","funders":"","keywords":"Integer programming; Planner; Scheduling (production processes); Linear programming; Mathematical optimization; Block (permutation group theory); Schedule; Net present value; Computer science; Production (economics); Engineering; Operations research; Mathematics; Artificial intelligence","score_opus":0.03291618499245851,"score_gpt":0.2588687798311251,"score_spread":0.2259525948386666,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2141292481","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":[0.004533026,0.00036266886,0.98088145,0.0003286583,0.00008788153,0.00015511042,0.00044174085,0.00021912201,0.012990266],"genre_scores_gemma":[0.27981597,0.00095767126,0.6908464,0.0003740611,0.00015373588,0.0020975182,0.0011897407,0.00028382288,0.024281148],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990338,0.00041559365,0.000039988885,0.00014580629,0.00025443282,0.000110373905],"domain_scores_gemma":[0.9983798,0.001191996,0.00013919866,0.000038484246,0.00020259911,0.000047827914],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0016819086,0.0016461287,0.0012580066,0.0006739242,0.00041778546,0.0016184124,0.0015319473,0.0018797661,0.010156764],"category_scores_gemma":[0.0027857597,0.00079178193,0.001271467,0.0013761708,0.000661893,0.00086528657,0.0010439487,0.0021901387,0.0014224884],"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":[0.000022722312,0.000023068209,0.00009725045,0.00007996301,0.000014460132,0.0000504675,0.000018943152,0.9836193,0.00033674226,0.009382698,0.00084542594,0.005508967],"study_design_scores_gemma":[0.000012737357,0.000023733286,0.00005155502,0.000008990751,0.0000049388736,0.000010885638,0.00001005569,0.9942526,0.00013258842,0.003900011,0.00158755,0.0000042334036],"about_ca_topic_score_codex":0.008158934,"about_ca_topic_score_gemma":0.008374622,"teacher_disagreement_score":0.010156764,"about_ca_system_score_codex":0.001384527,"about_ca_system_score_gemma":0.0025645408,"threshold_uncertainty_score":0.033977687},"labels":[],"label_agreement":null},{"id":"W2510141417","doi":"10.1504/ijmme.2016.078352","title":"Diggability assessment in open pit mines: a review","year":2016,"lang":"en","type":"review","venue":"International Journal of Mining and Mineral Engineering","topic":"Tunneling and Rock Mechanics","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta; University of British Columbia","funders":"","keywords":"Open-pit mining; Mining engineering; Geology; Forensic engineering; Engineering","score_opus":0.02868442380815063,"score_gpt":0.3389148372352048,"score_spread":0.3102304134270542,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2510141417","genre_codex":"review","genre_gemma":"review","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"review","genre_consensus":"review","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00026492463,0.9991429,0.00012244357,0.00008107146,0.000038182723,0.0000073753813,0.000021680178,0.0000031663724,0.00031830213],"genre_scores_gemma":[0.0017929537,0.9976157,0.00032677563,0.000054053155,0.00003798261,0.000007700102,0.000024569908,0.0000011548078,0.00013916563],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9992361,0.00014036507,0.00019853501,0.00012809828,0.00026803263,0.000028888313],"domain_scores_gemma":[0.997336,0.0015560688,0.000496747,0.000039371826,0.00051165,0.000060187755],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0014384497,0.0011547172,0.0021728913,0.0069299825,0.0003405454,0.0014662308,0.0014027635,0.0013206161,0.002772111],"category_scores_gemma":[0.0029320645,0.0005593467,0.0014002442,0.005217843,0.00062645174,0.0019081796,0.0006613249,0.0007716185,0.0006946933],"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":[0.00007999364,0.00013231479,0.001077397,0.16039385,0.00036925983,0.0003182502,0.0001952655,0.00064098806,0.0015278619,0.0013235158,0.008459324,0.82548195],"study_design_scores_gemma":[0.00003338421,0.0006125432,0.011622348,0.08832142,0.0025428392,0.005162031,0.0007978984,0.0006075596,0.0028192266,0.002383904,0.8849722,0.00012472419],"about_ca_topic_score_codex":0.0028071443,"about_ca_topic_score_gemma":0.005123325,"teacher_disagreement_score":0.0069299825,"about_ca_system_score_codex":0.00060087873,"about_ca_system_score_gemma":0.0019719594,"threshold_uncertainty_score":0.009273648},"labels":[],"label_agreement":null},{"id":"W2587829941","doi":"10.1504/ijmme.2017.10003210","title":"Heuristic stope layout optimisation accounting for variable stope dimensions and dilution management","year":2017,"lang":"en","type":"article","venue":"International Journal of Mining and Mineral Engineering","topic":"Mining Techniques and Economics","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Profitability index; Engineering; Profit (economics); Dilution; Variable (mathematics); Civil engineering; Mathematics","score_opus":0.011719658515059178,"score_gpt":0.23162693735197815,"score_spread":0.21990727883691896,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2587829941","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":[0.18584059,0.0008577645,0.7940273,0.00033815144,0.00009500995,0.00020362619,0.00035599814,0.000445657,0.017835839],"genre_scores_gemma":[0.8810432,0.00028892228,0.111847825,0.000066127934,0.000022230543,0.00016149199,0.00026677275,0.000112452646,0.006190919],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999723,0.00009526984,0.000010240919,0.000053770564,0.00004627106,0.000071414135],"domain_scores_gemma":[0.99925727,0.0005059123,0.00008473697,0.00003967128,0.00006802964,0.000044463464],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000640313,0.0008352467,0.0013640326,0.00075909414,0.00034189995,0.0013321261,0.00080405374,0.0016903791,0.0032110936],"category_scores_gemma":[0.0015043991,0.00070916035,0.000830127,0.0009182679,0.00058649003,0.0008366952,0.0006820491,0.0006722612,0.00028518576],"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":[0.000030084952,0.0000140604225,0.00017479908,0.000024685049,0.000011806968,0.0000385751,0.000009430094,0.9947119,0.00045637283,0.0007986032,0.00018638006,0.0035433697],"study_design_scores_gemma":[0.000009601639,0.000024145289,0.0001322386,0.0000036934962,0.00000616416,0.000011175165,0.00001247021,0.9984818,0.00017386,0.00089262973,0.00024828268,0.0000038999488],"about_ca_topic_score_codex":0.00401533,"about_ca_topic_score_gemma":0.0048903297,"teacher_disagreement_score":0.00401533,"about_ca_system_score_codex":0.00078631344,"about_ca_system_score_gemma":0.0009844529,"threshold_uncertainty_score":0.010742128},"labels":[],"label_agreement":null},{"id":"W2588119007","doi":"10.1504/ijmme.2017.10003266","title":"Analysing equipment allocation through queuing theory and Monte-Carlo simulations in surface mining operations","year":2017,"lang":"en","type":"article","venue":"International Journal of Mining and Mineral Engineering","topic":"Mining Techniques and Economics","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Truck; Shovel; Queueing theory; Queue; Engineering; Monte Carlo method; Idle; Transport engineering; Operations research; Computer science; Automotive engineering; Statistics; Mathematics; Mechanical engineering","score_opus":0.018542176271244926,"score_gpt":0.27109317371398517,"score_spread":0.25255099744274023,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2588119007","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":[0.65166914,0.00056752726,0.34005484,0.00047369054,0.00006289312,0.00018881536,0.00022593846,0.00030292335,0.006454133],"genre_scores_gemma":[0.9730661,0.00020558591,0.025226813,0.00003921932,0.000017138082,0.00009658444,0.000097286356,0.000028746002,0.0012224748],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99906856,0.0004832375,0.000041329924,0.00009575126,0.00015234902,0.00015878653],"domain_scores_gemma":[0.99004525,0.0087571135,0.0005101951,0.000139572,0.0003993323,0.00014848622],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0028229402,0.0006868352,0.0008462185,0.0012509456,0.0007374415,0.0013993698,0.001096413,0.001616069,0.001535728],"category_scores_gemma":[0.0063659013,0.0007606982,0.0009048592,0.0012348226,0.0008574242,0.0011283557,0.0006322306,0.0011103351,0.00014872101],"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":[0.0000152489,0.000024929246,0.00060408865,0.0000061579585,0.0000055195214,0.000017105001,0.000012958926,0.9969029,0.000092762,0.0013974708,0.000035173714,0.0008855916],"study_design_scores_gemma":[0.0000014173181,0.000006594565,0.000109843306,0.0000011138288,0.0000015806577,0.0000020006535,0.000007006281,0.99947697,0.000033271644,0.0003370742,0.000021002805,0.0000022015945],"about_ca_topic_score_codex":0.044886187,"about_ca_topic_score_gemma":0.02357028,"teacher_disagreement_score":0.044886187,"about_ca_system_score_codex":0.0029261266,"about_ca_system_score_gemma":0.0021222369,"threshold_uncertainty_score":0.08924979},"labels":[],"label_agreement":null},{"id":"W2797460359","doi":"10.1504/ijmme.2018.10012318","title":"Oil sands production scheduling and waste management with optimum cut-off grade policy","year":2018,"lang":"en","type":"article","venue":"International Journal of Mining and Mineral Engineering","topic":"Mining Techniques and Economics","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Laurentian University","funders":"","keywords":"Oil production; Waste management; Petroleum engineering; Production (economics); Environmental science; Oil supply; Operations management; Engineering; Business; Economics","score_opus":0.008273901926761588,"score_gpt":0.22207329640595316,"score_spread":0.21379939447919158,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2797460359","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":[0.6126646,0.0003980478,0.36500502,0.00028547423,0.000050981947,0.00037531395,0.00060385664,0.00038083762,0.020235889],"genre_scores_gemma":[0.95315725,0.00013692488,0.042734947,0.00001737872,0.0000045121587,0.00007330431,0.00017830396,0.00003739921,0.0036600113],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99971706,0.00006281573,0.000011984544,0.000044966284,0.00005766098,0.00010545066],"domain_scores_gemma":[0.99967444,0.00013289902,0.000071318376,0.00002058004,0.000060483268,0.00004034533],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00044910907,0.0005234029,0.000738645,0.0007039282,0.0003942891,0.0011048665,0.0007456711,0.000780031,0.0022246873],"category_scores_gemma":[0.0009944726,0.0005079657,0.0006435939,0.00065274467,0.00040899488,0.0007680711,0.00038747076,0.0004994044,0.00024515085],"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":[0.000078135155,0.000030039157,0.00048446696,0.000030149824,0.000008639206,0.00005133894,0.000017586437,0.99105936,0.0016588185,0.0012512228,0.00015126842,0.0051789484],"study_design_scores_gemma":[0.000016491396,0.000080941594,0.00043997425,0.0000058268215,0.0000088949055,0.000018139965,0.000032075866,0.9959758,0.0014610986,0.0014961885,0.00045774892,0.0000068404793],"about_ca_topic_score_codex":0.014375604,"about_ca_topic_score_gemma":0.014830283,"teacher_disagreement_score":0.014375604,"about_ca_system_score_codex":0.0015217012,"about_ca_system_score_gemma":0.0021049217,"threshold_uncertainty_score":0.028583825},"labels":[],"label_agreement":null},{"id":"W3113177538","doi":"10.1504/ijmme.2020.10034276","title":"A stochastic integrated simulation and mixed integer linear programming optimisation framework for truck dispatching problem in surface mines","year":2020,"lang":"en","type":"article","venue":"International Journal of Mining and Mineral Engineering","topic":"Mining Techniques and Economics","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Canadian Natural Resources; University of Alberta","funders":"","keywords":"Truck; Shovel; Integer programming; Operations research; Linear programming; Integer (computer science); Engineering; Simulation modeling; Stochastic programming; Computer science; Mathematical optimization; Automotive engineering; Algorithm","score_opus":0.019565682674086298,"score_gpt":0.2578378752749151,"score_spread":0.2382721926008288,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W3113177538","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":[0.017577812,0.0002431194,0.9765024,0.00020572507,0.000042137526,0.0000577943,0.00010626136,0.00017419261,0.0050904746],"genre_scores_gemma":[0.81724226,0.00052746374,0.17575768,0.000100827034,0.0000658009,0.00040985574,0.0003303604,0.00013898866,0.005426766],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993537,0.00030560303,0.000026071833,0.00007937826,0.00014976514,0.00008544435],"domain_scores_gemma":[0.99903935,0.00062316656,0.00009726964,0.000026389427,0.00016874573,0.000045055134],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012248748,0.0010757748,0.0012161649,0.0004854056,0.00042988083,0.00137644,0.0010911812,0.0012697804,0.0021539407],"category_scores_gemma":[0.0020602096,0.0007268002,0.0014367597,0.0007330376,0.00073694316,0.0007139508,0.0009289604,0.0014815151,0.00026853406],"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":[0.0000044697276,0.000003410945,0.00003142755,0.000005453165,0.00000324751,0.000005806431,0.0000029791165,0.9983676,0.000066300876,0.0009918809,0.000025595022,0.00049173547],"study_design_scores_gemma":[0.0000019151423,0.0000038449734,0.000013936353,0.000001094276,0.000001046565,0.0000012580297,0.000001383045,0.99944943,0.000030025052,0.0004150392,0.0000799538,0.0000011084595],"about_ca_topic_score_codex":0.017564455,"about_ca_topic_score_gemma":0.009426525,"teacher_disagreement_score":0.017564455,"about_ca_system_score_codex":0.0010917386,"about_ca_system_score_gemma":0.0022538546,"threshold_uncertainty_score":0.034924448},"labels":[],"label_agreement":null},{"id":"W4233565183","doi":"10.1504/ijmme.2018.091214","title":"Required strength estimation of a cemented backfill with the front wall exposed and back wall pressured","year":2018,"lang":"en","type":"article","venue":"International Journal of Mining and Mineral Engineering","topic":"Rock Mechanics and Modeling","field":"Engineering","cited_by":39,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Polytechnique Montréal","funders":"Fonds de recherche du Québec – Nature et technologies; Natural Sciences and Engineering Research Council of Canada; China Scholarship Council","keywords":"Geotechnical engineering; Overburden; Geology; Friction angle","score_opus":0.011532711039437676,"score_gpt":0.2131984700253732,"score_spread":0.20166575898593553,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4233565183","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":[0.6067084,0.0007503513,0.3858944,0.0001323156,0.000025818983,0.000071984105,0.00036145176,0.0006199996,0.0054352423],"genre_scores_gemma":[0.9741107,0.00011169819,0.025013506,0.000011589773,0.0000035644496,0.000029663903,0.00009958367,0.000034521567,0.00058516854],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999398,0.000065174354,0.000034052224,0.000095657415,0.00033921874,0.00006792227],"domain_scores_gemma":[0.99917716,0.0003074531,0.0001958937,0.000058512764,0.00022487273,0.00003604547],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008078118,0.00074814697,0.0006737679,0.001032293,0.00021552402,0.00080205564,0.00072684,0.0009898941,0.0015044177],"category_scores_gemma":[0.0017350552,0.00038699305,0.0005269488,0.0003498576,0.0004524791,0.0007979908,0.00046819574,0.00028367585,0.00044367736],"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":[0.0006648293,0.00014290992,0.010076318,0.0007855659,0.000050015908,0.0007923363,0.00017528018,0.4076436,0.48794255,0.0030259572,0.0007422258,0.087958306],"study_design_scores_gemma":[0.00003905644,0.0005347047,0.008247905,0.00005573882,0.00006448942,0.00041122694,0.0002117582,0.7989596,0.18801926,0.0014874873,0.0019140815,0.000054605607],"about_ca_topic_score_codex":0.000722658,"about_ca_topic_score_gemma":0.001438773,"teacher_disagreement_score":0.0015044177,"about_ca_system_score_codex":0.00036565642,"about_ca_system_score_gemma":0.0006030486,"threshold_uncertainty_score":0.005032778},"labels":[],"label_agreement":null},{"id":"W4239470645","doi":"10.1504/ijmme.2017.082680","title":"Heuristic stope layout optimisation accounting for variable stope dimensions and dilution management","year":2017,"lang":"en","type":"article","venue":"International Journal of Mining and Mineral Engineering","topic":"Mining Techniques and Economics","field":"Engineering","cited_by":15,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Profitability index; Engineering; Profit (economics); Dilution; Variable (mathematics); Civil engineering; Mathematics","score_opus":0.011719658515059178,"score_gpt":0.23162693735197815,"score_spread":0.21990727883691896,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4239470645","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":[0.18584059,0.0008577645,0.7940273,0.00033815144,0.00009500995,0.00020362619,0.00035599814,0.000445657,0.017835839],"genre_scores_gemma":[0.8810432,0.00028892228,0.111847825,0.000066127934,0.000022230543,0.00016149199,0.00026677275,0.000112452646,0.006190919],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999723,0.00009526984,0.000010240919,0.000053770564,0.00004627106,0.000071414135],"domain_scores_gemma":[0.99925727,0.0005059123,0.00008473697,0.00003967128,0.00006802964,0.000044463464],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000640313,0.0008352467,0.0013640326,0.00075909414,0.00034189995,0.0013321261,0.00080405374,0.0016903791,0.0032110936],"category_scores_gemma":[0.0015043991,0.00070916035,0.000830127,0.0009182679,0.00058649003,0.0008366952,0.0006820491,0.0006722612,0.00028518576],"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":[0.000030084952,0.0000140604225,0.00017479908,0.000024685049,0.000011806968,0.0000385751,0.000009430094,0.9947119,0.00045637283,0.0007986032,0.00018638006,0.0035433697],"study_design_scores_gemma":[0.000009601639,0.000024145289,0.0001322386,0.0000036934962,0.00000616416,0.000011175165,0.00001247021,0.9984818,0.00017386,0.00089262973,0.00024828268,0.0000038999488],"about_ca_topic_score_codex":0.00401533,"about_ca_topic_score_gemma":0.0048903297,"teacher_disagreement_score":0.00401533,"about_ca_system_score_codex":0.00078631344,"about_ca_system_score_gemma":0.0009844529,"threshold_uncertainty_score":0.010742128},"labels":[],"label_agreement":null},{"id":"W4244310446","doi":"10.1504/ijmme.2020.111929","title":"A stochastic integrated simulation and mixed integer linear programming optimisation framework for truck dispatching problem in surface mines","year":2020,"lang":"en","type":"article","venue":"International Journal of Mining and Mineral Engineering","topic":"Mining Techniques and Economics","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Canadian Natural Resources; University of Alberta","funders":"","keywords":"Truck; Shovel; Integer programming; Linear programming; Operations research; Engineering; Integer (computer science); Simulation modeling; Computer science; Mathematical optimization; Automotive engineering; Algorithm; Mathematics","score_opus":0.019565682674086298,"score_gpt":0.2578378752749151,"score_spread":0.2382721926008288,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4244310446","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":[0.017577812,0.0002431194,0.9765024,0.00020572507,0.000042137526,0.0000577943,0.00010626136,0.00017419261,0.0050904746],"genre_scores_gemma":[0.81724226,0.00052746374,0.17575768,0.000100827034,0.0000658009,0.00040985574,0.0003303604,0.00013898866,0.005426766],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9993537,0.00030560303,0.000026071833,0.00007937826,0.00014976514,0.00008544435],"domain_scores_gemma":[0.99903935,0.00062316656,0.00009726964,0.000026389427,0.00016874573,0.000045055134],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0012248748,0.0010757748,0.0012161649,0.0004854056,0.00042988083,0.00137644,0.0010911812,0.0012697804,0.0021539407],"category_scores_gemma":[0.0020602096,0.0007268002,0.0014367597,0.0007330376,0.00073694316,0.0007139508,0.0009289604,0.0014815151,0.00026853406],"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":[0.0000044697276,0.000003410945,0.00003142755,0.000005453165,0.00000324751,0.000005806431,0.0000029791165,0.9983676,0.000066300876,0.0009918809,0.000025595022,0.00049173547],"study_design_scores_gemma":[0.0000019151423,0.0000038449734,0.000013936353,0.000001094276,0.000001046565,0.0000012580297,0.000001383045,0.99944943,0.000030025052,0.0004150392,0.0000799538,0.0000011084595],"about_ca_topic_score_codex":0.017564455,"about_ca_topic_score_gemma":0.009426525,"teacher_disagreement_score":0.017564455,"about_ca_system_score_codex":0.0010917386,"about_ca_system_score_gemma":0.0022538546,"threshold_uncertainty_score":0.034924448},"labels":[],"label_agreement":null},{"id":"W4247584660","doi":"10.1504/ijmme.2018.091217","title":"Draw rate management system using mathematical programming in extraction sequence optimisation of block cave mining","year":2018,"lang":"en","type":"article","venue":"International Journal of Mining and Mineral Engineering","topic":"Mining Techniques and Economics","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Block (permutation group theory); Scheduling (production processes); Cave; Integer programming; Computer science; Engineering; Control (management); Mathematical optimization; Operations research; Industrial engineering; Algorithm; Mathematics; Artificial intelligence; Operations management; Archaeology; Geography","score_opus":0.022384675866127194,"score_gpt":0.26441817115209243,"score_spread":0.24203349528596524,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4247584660","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":[0.06950429,0.00022580539,0.9227484,0.00017008264,0.000024189148,0.00012267368,0.00008377379,0.00037298742,0.0067477007],"genre_scores_gemma":[0.90018183,0.0002529997,0.09578415,0.000039174276,0.0000130749195,0.000210264,0.000084826745,0.000062272935,0.0033714846],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995896,0.00015863181,0.00002067634,0.00007000536,0.00010289159,0.00005819604],"domain_scores_gemma":[0.9992853,0.00044156986,0.00011713193,0.000025901383,0.000098997785,0.000031205927],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0011657948,0.00073494046,0.0008319676,0.0005285955,0.0004218746,0.0014992729,0.0007872341,0.00083199545,0.0016362406],"category_scores_gemma":[0.0017362084,0.00056442665,0.0006198573,0.0006343352,0.00045513862,0.00077225774,0.0007867245,0.0007053195,0.0001867117],"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":[0.000017284054,0.0000117481295,0.000120405864,0.0000174458,0.000004216974,0.000015692933,0.000015776499,0.99338984,0.0003847412,0.0014406538,0.00007394392,0.0045082523],"study_design_scores_gemma":[0.0000025797729,0.00001559394,0.000030636278,0.0000015976465,0.0000024795952,0.0000026555915,0.000003459533,0.9993024,0.00017229794,0.0003418632,0.00012268288,0.0000017883119],"about_ca_topic_score_codex":0.009118384,"about_ca_topic_score_gemma":0.006526004,"teacher_disagreement_score":0.009118384,"about_ca_system_score_codex":0.0011716093,"about_ca_system_score_gemma":0.0016849756,"threshold_uncertainty_score":0.0181306},"labels":[],"label_agreement":null},{"id":"W4251478281","doi":"10.1504/ijmme.2017.082693","title":"Analysing equipment allocation through queuing theory and Monte-Carlo simulations in surface mining operations","year":2017,"lang":"en","type":"article","venue":"International Journal of Mining and Mineral Engineering","topic":"Mining Techniques and Economics","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Truck; Shovel; Queueing theory; Queue; Engineering; Monte Carlo method; Idle; Transport engineering; Operations research; Computer science; Automotive engineering; Statistics; Mathematics; Mechanical engineering","score_opus":0.018542176271244926,"score_gpt":0.27109317371398517,"score_spread":0.25255099744274023,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4251478281","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":[0.65166914,0.00056752726,0.34005484,0.00047369054,0.00006289312,0.00018881536,0.00022593846,0.00030292335,0.006454133],"genre_scores_gemma":[0.9730661,0.00020558591,0.025226813,0.00003921932,0.000017138082,0.00009658444,0.000097286356,0.000028746002,0.0012224748],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99906856,0.0004832375,0.000041329924,0.00009575126,0.00015234902,0.00015878653],"domain_scores_gemma":[0.99004525,0.0087571135,0.0005101951,0.000139572,0.0003993323,0.00014848622],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0028229402,0.0006868352,0.0008462185,0.0012509456,0.0007374415,0.0013993698,0.001096413,0.001616069,0.001535728],"category_scores_gemma":[0.0063659013,0.0007606982,0.0009048592,0.0012348226,0.0008574242,0.0011283557,0.0006322306,0.0011103351,0.00014872101],"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":[0.0000152489,0.000024929246,0.00060408865,0.0000061579585,0.0000055195214,0.000017105001,0.000012958926,0.9969029,0.000092762,0.0013974708,0.000035173714,0.0008855916],"study_design_scores_gemma":[0.0000014173181,0.000006594565,0.000109843306,0.0000011138288,0.0000015806577,0.0000020006535,0.000007006281,0.99947697,0.000033271644,0.0003370742,0.000021002805,0.0000022015945],"about_ca_topic_score_codex":0.044886187,"about_ca_topic_score_gemma":0.02357028,"teacher_disagreement_score":0.044886187,"about_ca_system_score_codex":0.0029261266,"about_ca_system_score_gemma":0.0021222369,"threshold_uncertainty_score":0.08924979},"labels":[],"label_agreement":null},{"id":"W4251854831","doi":"10.1504/ijmme.2021.121325","title":"Short-term production scheduling in open pit mines with shovel allocations over continuous time frames","year":2021,"lang":"en","type":"article","venue":"International Journal of Mining and Mineral Engineering","topic":"Mining Techniques and Economics","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Scheduling (production processes); Shovel; Pareto principle; Mathematical optimization; Computer science; Engineering; Production (economics); Pareto optimal; Term (time); Operations research; Multi-objective optimization; Operations management; Mathematics; Economics","score_opus":0.01076689482001382,"score_gpt":0.2366354688887815,"score_spread":0.2258685740687677,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4251854831","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":[0.49485344,0.00032707292,0.4936797,0.00028855828,0.000037163034,0.00021104592,0.000289064,0.0001631359,0.010150716],"genre_scores_gemma":[0.9697878,0.00012588294,0.027438449,0.0000115953035,0.000005602312,0.00007432677,0.000068810616,0.000021476695,0.0024661885],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9995339,0.00014412418,0.000018331357,0.0000896903,0.00007398931,0.00013999054],"domain_scores_gemma":[0.99935097,0.000295979,0.00011973103,0.000042144013,0.000068757116,0.00012238463],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008989765,0.0004589908,0.0006586193,0.00036404497,0.0006385198,0.001186376,0.0012265502,0.0011152198,0.0023980653],"category_scores_gemma":[0.0014313312,0.0005294585,0.00055370486,0.00067097397,0.00077252754,0.0010495835,0.0008313955,0.00078538933,0.00020667122],"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":[0.00010465958,0.000060436436,0.00045550324,0.000034145447,0.000009577674,0.00012699052,0.000058993424,0.98718566,0.0018848358,0.003679079,0.00017173086,0.0062283725],"study_design_scores_gemma":[0.000018865232,0.00021191452,0.0007046758,0.000006561479,0.000008258243,0.000034439414,0.00015425021,0.99432206,0.000639766,0.0032994105,0.00058962574,0.0000101163005],"about_ca_topic_score_codex":0.010474487,"about_ca_topic_score_gemma":0.011894247,"teacher_disagreement_score":0.010474487,"about_ca_system_score_codex":0.0012410447,"about_ca_system_score_gemma":0.0014379922,"threshold_uncertainty_score":0.020826995},"labels":[],"label_agreement":null},{"id":"W4256098857","doi":"10.1504/ijmme.2018.091218","title":"Oil sands production scheduling and waste management with optimum cut-off grade policy","year":2018,"lang":"en","type":"article","venue":"International Journal of Mining and Mineral Engineering","topic":"Mining Techniques and Economics","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Laurentian University","funders":"","keywords":"Stockpile; Tailings; Overburden; Oil sands; Net present value; Waste management; Open-pit mining; Engineering; Land reclamation; Environmental science; Schedule; Mining engineering; Production (economics); Geography","score_opus":0.008273901926761588,"score_gpt":0.22207329640595316,"score_spread":0.21379939447919158,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4256098857","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":[0.6126646,0.0003980478,0.36500502,0.00028547423,0.000050981947,0.00037531395,0.00060385664,0.00038083762,0.020235889],"genre_scores_gemma":[0.95315725,0.00013692488,0.042734947,0.00001737872,0.0000045121587,0.00007330431,0.00017830396,0.00003739921,0.0036600113],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99971706,0.00006281573,0.000011984544,0.000044966284,0.00005766098,0.00010545066],"domain_scores_gemma":[0.99967444,0.00013289902,0.000071318376,0.00002058004,0.000060483268,0.00004034533],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00044910907,0.0005234029,0.000738645,0.0007039282,0.0003942891,0.0011048665,0.0007456711,0.000780031,0.0022246873],"category_scores_gemma":[0.0009944726,0.0005079657,0.0006435939,0.00065274467,0.00040899488,0.0007680711,0.00038747076,0.0004994044,0.00024515085],"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":[0.000078135155,0.000030039157,0.00048446696,0.000030149824,0.000008639206,0.00005133894,0.000017586437,0.99105936,0.0016588185,0.0012512228,0.00015126842,0.0051789484],"study_design_scores_gemma":[0.000016491396,0.000080941594,0.00043997425,0.0000058268215,0.0000088949055,0.000018139965,0.000032075866,0.9959758,0.0014610986,0.0014961885,0.00045774892,0.0000068404793],"about_ca_topic_score_codex":0.014375604,"about_ca_topic_score_gemma":0.014830283,"teacher_disagreement_score":0.014375604,"about_ca_system_score_codex":0.0015217012,"about_ca_system_score_gemma":0.0021049217,"threshold_uncertainty_score":0.028583825},"labels":[],"label_agreement":null}]}