{"meta":{"query_hash":"089ebc39aae2","filters":{"venue":"Mathematical Geology"},"cohort_total":28,"direct_labels_cover":0,"predictions_cover":28,"exported":28,"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/089ebc39aae2","api":"https://metacan.xera.ac/api/v1/cohort?venue=Mathematical+Geology"},"results":[{"id":"W1253774118","doi":"10.1023/a:1026290803830","title":"Letter to the Editor: Comment on “Understanding Anisotropy Computations” by M. Eriksson and P. P. Siska","year":2003,"lang":"en","type":"article","venue":"Mathematical Geology","topic":"Soil Geostatistics and Mapping","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":"Polytechnique Montréal","funders":"","keywords":"Geology","score_opus":0.019775835552579512,"score_gpt":0.24203249428420556,"score_spread":0.22225665873162606,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1253774118","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.010813056,0.00002570864,0.84988946,0.08416581,0.00070936815,0.0005545467,0.000010816751,0.00004806952,0.05378317],"genre_scores_gemma":[0.9220898,0.000010009224,0.021360496,0.0552449,0.00034314508,0.0000697087,0.00000781105,0.000023214487,0.000850914],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99923176,0.00007962292,0.00013760924,0.00017960973,0.00014896554,0.00022245682],"domain_scores_gemma":[0.9993411,0.00040902707,0.000030382316,0.00013719476,0.000002787216,0.00007951702],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00023127654,0.00009306418,0.00011310689,0.000013203818,0.00018352969,0.000028109785,0.00008442218,0.000042041476,0.00089927536],"category_scores_gemma":[0.00011718353,0.00006469486,0.000015385445,0.000065296386,0.00014484285,0.000018183797,0.00008320038,0.00009538415,0.0005678552],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000003476859,0.000051299525,0.00038925436,0.000005217398,0.0000062177205,0.0000017571014,0.0004229854,0.00022417938,0.00008914816,0.12288679,0.8757503,0.00016937318],"study_design_scores_gemma":[0.00028144673,0.00018551566,0.0005147998,0.000010653687,0.000012229704,0.000009422447,0.0003820729,0.004286509,0.0000960923,0.1479928,0.8460683,0.0001601516],"about_ca_topic_score_codex":0.00002177737,"about_ca_topic_score_gemma":0.000005695798,"teacher_disagreement_score":0.91127676,"about_ca_system_score_codex":0.000074788964,"about_ca_system_score_gemma":0.0000019050556,"threshold_uncertainty_score":0.98464346},"labels":[],"label_agreement":null},{"id":"W146226219","doi":"10.1023/a:1007502817679","title":"Integrating Large-Scale Soft Data by Simulated Annealing and Probability Constraints","year":2000,"lang":"en","type":"article","venue":"Mathematical Geology","topic":"Reservoir Engineering and Simulation Methods","field":"Engineering","cited_by":19,"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":"Probability distribution; Cumulative distribution function; Statistics; Computer science; Probability density function; Mathematics; Random variable; Algorithm; Mathematical optimization; Data mining","score_opus":0.023358942927671628,"score_gpt":0.28287001980505055,"score_spread":0.25951107687737895,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W146226219","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.57890755,0.00014340009,0.41678002,0.00006896588,0.000036008052,0.00013771842,0.000031319076,0.00032195754,0.0035730475],"genre_scores_gemma":[0.8797724,0.000014392226,0.11978936,0.00003464358,0.00003247454,0.000005511332,0.000076895696,0.000027509761,0.00024678052],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9989381,0.0000677776,0.00033492292,0.0002535096,0.00009004839,0.00031565412],"domain_scores_gemma":[0.9989121,0.00049706356,0.0000151986615,0.00044841334,0.000021655065,0.00010559712],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00060337404,0.000153696,0.00028435414,0.000028326684,0.00005215832,0.000028632357,0.0002034848,0.0001478711,0.0016158833],"category_scores_gemma":[0.0003583705,0.00013658065,0.000022055896,0.00009950252,0.00012706764,0.00009261248,0.00006475847,0.00023033624,0.000049854316],"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":[0.000012838888,0.000079286554,0.0013358021,0.00047605962,0.00006621349,0.0000071990858,0.00090112095,0.96678495,0.0006600926,0.001940769,0.00079310336,0.02694259],"study_design_scores_gemma":[0.00031507373,0.00001362313,0.00008216395,0.000023502795,0.000009553177,0.000012657131,0.000038992246,0.9873135,0.00007539741,0.009954841,0.0020231002,0.00013756227],"about_ca_topic_score_codex":0.000002600515,"about_ca_topic_score_gemma":0.0000018751587,"teacher_disagreement_score":0.30086488,"about_ca_system_score_codex":0.000012253668,"about_ca_system_score_gemma":0.0000059552585,"threshold_uncertainty_score":0.9992968},"labels":[],"label_agreement":null},{"id":"W1513781221","doi":"10.1023/a:1011094131273","title":"Rate of Convergence of the Gibbs Sampler in the Gaussian Case","year":2001,"lang":"en","type":"article","venue":"Mathematical Geology","topic":"Soil Geostatistics and Mapping","field":"Environmental Science","cited_by":35,"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","funders":"","keywords":"Applied mathematics; Mathematics; Covariance; Gaussian; Rate of convergence; Context (archaeology); Convergence (economics); Gibbs sampling; Covariance matrix; Fixed point; Mathematical optimization; Mathematical analysis; Computer science; Algorithm; Statistics; Physics; Bayesian probability","score_opus":0.021477446301367366,"score_gpt":0.2533831049290888,"score_spread":0.23190565862772142,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1513781221","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.97704864,0.0000074341374,0.0043010153,0.001035577,0.00004671038,0.00014843959,0.0000027777644,0.000002734612,0.017406698],"genre_scores_gemma":[0.99854296,0.0000048294633,0.0009315729,0.00027896743,0.000004817843,0.000008353805,3.4734921e-7,0.0000026860869,0.00022545531],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9993237,0.00011161795,0.00022977428,0.00009507445,0.00008824584,0.00015156876],"domain_scores_gemma":[0.9992507,0.00040157326,0.000074974036,0.00024868318,0.000004714673,0.000019365616],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00041444504,0.00005624878,0.0001272193,0.000010864313,0.000031486845,0.0000021247913,0.00021806263,0.000035115674,0.0030873006],"category_scores_gemma":[0.00025263545,0.000029527928,0.000030159164,0.00017773315,0.00044011857,0.000015118963,0.00012796812,0.00007369703,0.000078706995],"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":[0.000044286116,0.0006495179,0.3758332,0.00016799444,0.000030887535,0.000787331,0.011753606,0.0009781374,0.0035924637,0.598098,0.0028952982,0.0051693195],"study_design_scores_gemma":[0.0005374376,0.0001110867,0.4121787,0.00003967664,0.000032287495,0.001539978,0.0016990176,0.013113809,0.00066607416,0.56577176,0.004125914,0.00018423867],"about_ca_topic_score_codex":0.0006305837,"about_ca_topic_score_gemma":0.000358887,"teacher_disagreement_score":0.036345497,"about_ca_system_score_codex":0.000007859519,"about_ca_system_score_gemma":0.0000052263476,"threshold_uncertainty_score":0.997824},"labels":[],"label_agreement":null},{"id":"W1513862039","doi":"10.1023/a:1010993113807","title":"Two Artifacts of Probability Field Simulation","year":2001,"lang":"en","type":"article","venue":"Mathematical Geology","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":"University of Alberta","funders":"","keywords":"Maxima and minima; Basis (linear algebra); Computer science; Probability distribution; Field (mathematics); Conditioning; Flexibility (engineering); Variogram; Range (aeronautics); Maxima; Algorithm; Probability and statistics; Mathematics; Statistics; Machine learning; Kriging; Engineering; Geometry","score_opus":0.02691804045526136,"score_gpt":0.2842677127952238,"score_spread":0.2573496723399624,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1513862039","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.79969573,0.0000021538906,0.13232714,0.00031732986,0.000030035857,0.00012336558,4.0252505e-7,0.000017501148,0.06748637],"genre_scores_gemma":[0.9853717,7.557779e-7,0.01416372,0.00014626366,0.000009536774,0.0000056831946,9.977449e-7,0.0000028526872,0.00029848923],"study_design_codex":"observational","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9994157,0.000025615016,0.00019054534,0.00012542604,0.00009835361,0.00014433535],"domain_scores_gemma":[0.9993093,0.0004329232,0.000047621856,0.00016139745,0.0000075468256,0.000041194628],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001598136,0.000053115546,0.00011846518,0.000010279882,0.000023378103,0.0000029437049,0.00007094148,0.000038981278,0.0073256358],"category_scores_gemma":[0.0005364109,0.00004461963,0.000023296152,0.00007452242,0.000112054295,0.000027671145,0.00008662966,0.00004734059,0.0004924202],"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":[0.000118856304,0.00099611,0.4353523,0.00018448924,0.000035742665,0.00003911745,0.0016017925,0.11713812,0.0039878422,0.34712926,0.00093334867,0.09248304],"study_design_scores_gemma":[0.00021340566,0.000098319615,0.034454584,0.000007623101,0.000009058005,0.000008063234,0.000021258606,0.12142669,0.0005002992,0.8418134,0.0013577914,0.000089536785],"about_ca_topic_score_codex":0.000069721435,"about_ca_topic_score_gemma":0.000033386757,"teacher_disagreement_score":0.49468413,"about_ca_system_score_codex":0.000012924878,"about_ca_system_score_gemma":0.0000027429667,"threshold_uncertainty_score":0.99358183},"labels":[],"label_agreement":null},{"id":"W1587069167","doi":"10.1023/a:1007587318807","title":"Fractal Geometry of Element Distribution on Mineral Surfaces","year":2001,"lang":"en","type":"article","venue":"Mathematical Geology","topic":"Geochemistry and Geologic Mapping","field":"Computer Science","cited_by":26,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"York University","keywords":"Mineral; Fractal; Mineralogy; Geology; Fractal analysis; Fractal dimension; Mathematics; Materials science; Metallurgy","score_opus":0.015918416534945013,"score_gpt":0.24516931877979134,"score_spread":0.22925090224484632,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1587069167","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.73784596,0.0000207775,0.23127034,0.0048889625,0.000092025875,0.000094639276,0.0000029178693,0.000065784974,0.025718614],"genre_scores_gemma":[0.99357337,0.0000032697733,0.004774712,0.000121397585,0.000029041095,0.000007852241,0.000013594523,0.0000012611159,0.0014755278],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99897856,0.000042047468,0.00028459553,0.00023531292,0.00017557036,0.0002839187],"domain_scores_gemma":[0.9991833,0.00024236758,0.00009896085,0.000345774,0.00006892523,0.000060648385],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00028110796,0.00011005686,0.00022201482,0.000031906442,0.000043566135,0.000014886168,0.0003924053,0.00009748244,0.00056097686],"category_scores_gemma":[0.0003444354,0.00008835594,0.000058773734,0.000214589,0.00009960566,0.000055189135,0.0001834926,0.000114110335,0.00013458135],"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":[0.000029601446,0.000705268,0.01026323,0.00012939237,0.000043542845,0.000071513,0.00022320586,0.0007863481,0.0036191507,0.9759388,0.0028162368,0.0053736907],"study_design_scores_gemma":[0.0013099366,0.0010725651,0.033707514,0.000102502396,0.000026608925,0.00034850137,0.00016474197,0.20720907,0.022450354,0.6743595,0.058557965,0.00069074694],"about_ca_topic_score_codex":0.000004982047,"about_ca_topic_score_gemma":5.098515e-7,"teacher_disagreement_score":0.30157933,"about_ca_system_score_codex":0.000013967211,"about_ca_system_score_gemma":0.0000134917655,"threshold_uncertainty_score":0.61423033},"labels":[],"label_agreement":null},{"id":"W194002261","doi":"10.1023/a:1014412218427","title":"Calculation of Uncertainty in the Variogram","year":2002,"lang":"en","type":"article","venue":"Mathematical Geology","topic":"Soil Geostatistics and Mapping","field":"Environmental Science","cited_by":58,"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":"Variogram; Kriging; Geostatistics; Mathematics; Statistics; Measure (data warehouse); Gaussian; Generalization; Gaussian process; Applied mathematics; Computer science; Data mining; Physics; Spatial variability; Mathematical analysis","score_opus":0.0207878691773006,"score_gpt":0.24201345569075153,"score_spread":0.22122558651345092,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W194002261","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.83185536,0.000032781285,0.022226393,0.001924324,0.000048651804,0.00028646213,0.0000013936763,0.000016488379,0.14360815],"genre_scores_gemma":[0.9978574,0.0000035472574,0.0017726294,0.00015010161,0.0000053450713,0.000010046839,8.769036e-7,0.0000019669428,0.00019811955],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9994931,0.0000468348,0.00015173765,0.000080438076,0.00010664887,0.0001212295],"domain_scores_gemma":[0.9995917,0.00023264535,0.000032291435,0.0001257948,0.0000026544278,0.000014917386],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00021092872,0.00004158785,0.00008652655,0.000014814587,0.000019187448,0.0000031551335,0.0001081196,0.00003484732,0.0035962947],"category_scores_gemma":[0.00013357976,0.000026902602,0.000019563453,0.00013511817,0.00015110786,0.000013654206,0.000044326745,0.000055507106,0.00033392877],"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":[0.000014940302,0.0013419093,0.10033032,0.00011432316,0.000025286825,0.0000611392,0.018488977,0.033783767,0.00059468945,0.7386845,0.011024807,0.09553538],"study_design_scores_gemma":[0.00029815044,0.00008599928,0.14230289,0.000011307055,0.0000116761985,0.000023478357,0.00020017856,0.46440768,0.000009894549,0.38715252,0.005385716,0.00011050946],"about_ca_topic_score_codex":0.00019213758,"about_ca_topic_score_gemma":0.00007090305,"teacher_disagreement_score":0.43062392,"about_ca_system_score_codex":0.000010793781,"about_ca_system_score_gemma":6.387004e-7,"threshold_uncertainty_score":0.9973146},"labels":[],"label_agreement":null},{"id":"W1972168640","doi":"10.1007/s11004-007-9115-7","title":"A Comparison between a Modified Counter Propagation Network and an Extended Self-Organizing Map in Remotely Sensed Data Classification","year":2007,"lang":"en","type":"article","venue":"Mathematical Geology","topic":"Neural Networks and Applications","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":"Western University","funders":"Jilin University; National Natural Science Foundation of China","keywords":"Self-organizing map; Computer science; Layer (electronics); Artificial intelligence; Pattern recognition (psychology); Artificial neural network; Data mining","score_opus":0.09274232628576105,"score_gpt":0.350159695735264,"score_spread":0.25741736944950294,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1972168640","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.20030464,0.000025892328,0.7972778,0.0014990668,0.000041581883,0.00036089137,0.00000108406,0.00014861477,0.00034041825],"genre_scores_gemma":[0.868655,0.0000022706672,0.13094746,0.00015709925,0.00015729941,0.000007988349,0.00004348948,0.000009182333,0.000020196787],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9983475,0.000108104,0.0004990871,0.00052335043,0.00015483097,0.00036712762],"domain_scores_gemma":[0.9984561,0.0003839217,0.00014604423,0.00085630483,0.00004925171,0.00010835398],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00093231903,0.00013266146,0.0002785085,0.00006372418,0.000107349515,0.00007674282,0.000613055,0.00013111623,0.000005876141],"category_scores_gemma":[0.00004094346,0.000118429656,0.0000128706315,0.0003403112,0.000075526026,0.00028597857,0.00032843635,0.00021537047,0.000030612126],"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":[0.00003854459,0.0007278858,0.027296001,0.0001553985,0.000038205235,0.00002982355,0.002220047,0.00036503345,0.0021242897,0.91686004,0.0012455875,0.04889916],"study_design_scores_gemma":[0.0002607627,0.00005740005,0.08176178,0.00002105989,0.000011392456,0.000017068227,0.000037502785,0.8359538,0.000064696054,0.08135898,0.0003105572,0.00014504728],"about_ca_topic_score_codex":0.000007932236,"about_ca_topic_score_gemma":0.00003945723,"teacher_disagreement_score":0.8355887,"about_ca_system_score_codex":0.000027322201,"about_ca_system_score_gemma":0.00002158723,"threshold_uncertainty_score":0.4829421},"labels":[],"label_agreement":null},{"id":"W198118184","doi":"10.1023/a:1007594423172","title":"A Pool-Based Model of the Spatial Distribution of Undiscovered Petroleum Resoufrces","year":2000,"lang":"en","type":"article","venue":"Mathematical Geology","topic":"Geochemistry and Geologic Mapping","field":"Computer Science","cited_by":22,"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","funders":"","keywords":"Parameterized complexity; Geology; Hydrogeology; Sampling (signal processing); Independence (probability theory); Entropy (arrow of time); Mathematics; Computer science; Statistics; Algorithm; Geotechnical engineering","score_opus":0.013323584437348561,"score_gpt":0.21338167796625052,"score_spread":0.20005809352890194,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W198118184","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.34346423,0.0000097677685,0.63945466,0.0034836675,0.000027369317,0.00009125393,0.0000115843695,0.000026481435,0.013430996],"genre_scores_gemma":[0.9961245,6.049325e-7,0.0024850494,0.00007217367,0.000010068752,0.0000072431335,0.000005095006,0.0000012688298,0.0012939963],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99906147,0.00007100619,0.00031149943,0.00018333351,0.00017678666,0.00019591402],"domain_scores_gemma":[0.99911207,0.0001606126,0.00012158991,0.0005193412,0.00005386828,0.000032511754],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00020867102,0.00009230063,0.00022562798,0.000013880639,0.000047508427,0.0000070630053,0.0006468703,0.00009290068,0.0003194015],"category_scores_gemma":[0.0002020914,0.00006116517,0.00010122959,0.00012644171,0.00026776217,0.000036848316,0.00013532277,0.000096778625,0.000015210627],"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":[0.0001077131,0.0007598877,0.0018876675,0.00054085744,0.000053755666,0.0000052297983,0.0006912094,0.31088266,0.0070572942,0.6734492,0.0006202975,0.003944235],"study_design_scores_gemma":[0.00022406525,0.00004500436,0.0011958552,0.000025341522,0.00000834971,0.0000053409085,0.000007064966,0.8004907,0.008574585,0.18914883,0.00021342216,0.000061455525],"about_ca_topic_score_codex":0.000022175307,"about_ca_topic_score_gemma":0.00000518907,"teacher_disagreement_score":0.65266025,"about_ca_system_score_codex":0.000009149614,"about_ca_system_score_gemma":0.000057482703,"threshold_uncertainty_score":0.34972227},"labels":[],"label_agreement":null},{"id":"W1998954134","doi":"10.1007/s11004-005-6669-0","title":"An Application of Multivariate Simulation in the Cement Industry","year":2005,"lang":"en","type":"article","venue":"Mathematical Geology","topic":"Geochemistry and Geologic Mapping","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"BioPhage Pharma (Canada); Polytechnique Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Autocorrelation; Mixing (physics); Covariance; Covariance matrix; Multivariate statistics; Computer science; Algorithm; Environmental science; Statistics; Mathematics","score_opus":0.02582256395717371,"score_gpt":0.30049315739131655,"score_spread":0.27467059343414285,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W1998954134","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.1257703,0.000005022863,0.8612471,0.005197226,0.00001158188,0.00016928528,1.5359375e-7,0.000026321213,0.007572993],"genre_scores_gemma":[0.9802451,1.4754217e-7,0.019377062,0.00025220827,0.00002835525,0.000027065811,0.000001787736,7.492083e-7,0.000067484165],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99928355,0.00008487673,0.00023393755,0.0001585634,0.00010198879,0.00013710825],"domain_scores_gemma":[0.9992343,0.00023082142,0.000075721124,0.00040022147,0.000037070644,0.000021835032],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00049546466,0.000059784572,0.000104408915,0.000027138069,0.000025871954,0.000009208563,0.00047770693,0.00013397403,0.000054468142],"category_scores_gemma":[0.00011702842,0.000041396226,0.000017499207,0.00014644612,0.00004737257,0.000083090395,0.00006646469,0.00015741934,0.000026489019],"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":[0.000004739313,0.000499426,0.0018470967,0.00004136311,0.00000497507,0.0000019647025,0.0026418273,0.16169903,0.002697775,0.8095239,0.000015710728,0.021022232],"study_design_scores_gemma":[0.00014258697,0.000030544754,0.0041017653,0.000004015261,0.000001734913,0.0000046430446,0.00005712341,0.8921588,0.0008040749,0.10086801,0.0017788756,0.000047813668],"about_ca_topic_score_codex":0.000007738897,"about_ca_topic_score_gemma":0.0000034833026,"teacher_disagreement_score":0.85447484,"about_ca_system_score_codex":0.000008279115,"about_ca_system_score_gemma":0.0000091486245,"threshold_uncertainty_score":0.1688089},"labels":[],"label_agreement":null},{"id":"W2026029976","doi":"10.1007/s11004-005-9000-1","title":"Undiscovered Petroleum Accumulation Mapping Using Model-Based Stochastic Simulation","year":2006,"lang":"en","type":"article","venue":"Mathematical Geology","topic":"Reservoir Engineering and Simulation Methods","field":"Engineering","cited_by":26,"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","funders":"","keywords":"Computer science; Petroleum; Spatial analysis; Stochastic simulation; Resource (disambiguation); Data mining; Geology; Statistics; Remote sensing; Mathematics","score_opus":0.054342921444039426,"score_gpt":0.31263356964319144,"score_spread":0.25829064819915204,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2026029976","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.36911255,0.000020373094,0.62995666,0.000013719805,0.0000666546,0.00008959389,0.0000017097803,0.0002417115,0.00049701397],"genre_scores_gemma":[0.8626419,1.14178924e-7,0.13710406,0.0000102142,0.000079759746,0.00000926452,0.000025890864,0.00003586387,0.00009297527],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99894494,0.000041616047,0.00038363086,0.00016566837,0.00016469437,0.00029944498],"domain_scores_gemma":[0.999225,0.00041302075,0.00004047342,0.0002305665,0.00003858826,0.000052351716],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021003149,0.00017863724,0.00025888308,0.00018503699,0.000059295355,0.000031799234,0.00009460669,0.00015253449,0.00007522869],"category_scores_gemma":[0.000110004934,0.00018206626,0.00007288746,0.00016499293,0.000035403424,0.000102591075,0.000018145432,0.00013861053,0.000044083252],"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":[0.000005057826,0.000018344317,0.00008508165,0.000095316434,0.00000923126,0.0000011924901,0.00002639724,0.99483293,0.0013115833,0.003559214,0.0000071516843,0.00004849421],"study_design_scores_gemma":[0.000419715,0.000007886672,0.00022416099,0.000025155545,0.000014637033,0.0000018268611,0.0000053713243,0.9651675,0.00009376292,0.033842783,0.000018926972,0.00017822957],"about_ca_topic_score_codex":0.00000442405,"about_ca_topic_score_gemma":8.772764e-7,"teacher_disagreement_score":0.4935293,"about_ca_system_score_codex":0.00008546907,"about_ca_system_score_gemma":0.000016002434,"threshold_uncertainty_score":0.74244463},"labels":[],"label_agreement":null},{"id":"W2032765727","doi":"10.1007/s11004-006-9065-5","title":"Fractal Modelling of the Microstructure Property of Quartz Mylonite During Deformation Process","year":2007,"lang":"en","type":"article","venue":"Mathematical Geology","topic":"Geochemistry and Geologic Mapping","field":"Computer Science","cited_by":30,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Mylonite; Geology; Fractal; Fractal dimension; Mineralogy; Quartz; Deformation (meteorology); Metamorphism; Multifractal system; Geometry; Geochemistry; Shear zone; Seismology; Mathematics; Tectonics; Mathematical analysis","score_opus":0.014109036964096879,"score_gpt":0.2209868651111523,"score_spread":0.2068778281470554,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2032765727","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6386642,0.00001119119,0.35722572,0.00040932416,0.000037269187,0.00010746854,4.1408836e-7,0.00001982126,0.0035245863],"genre_scores_gemma":[0.9888163,4.912599e-7,0.010832907,0.000028818065,0.00001549263,0.0000031542559,6.134819e-7,0.000001687098,0.0003005008],"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99901336,0.000027314862,0.00040817022,0.00015263316,0.00016455809,0.00023395852],"domain_scores_gemma":[0.99915725,0.00008794145,0.00022347334,0.00034309653,0.00015556165,0.000032659507],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00037522003,0.000096097196,0.00019655377,0.00003390656,0.00007249138,0.000007574936,0.00054509955,0.00011872319,0.000036331545],"category_scores_gemma":[0.00012431745,0.00005075756,0.000062644285,0.00021322364,0.00015444645,0.000106730906,0.00017416052,0.00015757492,0.000005214116],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00027366434,0.0012290098,0.03095726,0.0130964145,0.0002428834,0.000048739083,0.07789058,0.15992877,0.40581766,0.3036946,0.00009046849,0.0067299437],"study_design_scores_gemma":[0.0004335151,0.00006437665,0.0049056397,0.00015427865,0.00001416622,0.0002693144,0.0004666844,0.4067458,0.3376634,0.24896584,0.00009918304,0.00021781033],"about_ca_topic_score_codex":0.0000047572257,"about_ca_topic_score_gemma":0.0000011570492,"teacher_disagreement_score":0.35015213,"about_ca_system_score_codex":0.0000082027445,"about_ca_system_score_gemma":0.000026318576,"threshold_uncertainty_score":0.20698333},"labels":[],"label_agreement":null},{"id":"W2048676560","doi":"10.1007/s11004-006-9053-9","title":"Spectral Corrected Semivariogram Models","year":2006,"lang":"en","type":"article","venue":"Mathematical Geology","topic":"Spectroscopy and Chemometric Analyses","field":"Chemistry","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":"Variogram; Interpolation (computer graphics); Covariance; Mathematics; Geostatistics; Covariance function; Applied mathematics; Consistency (knowledge bases); Statistics; Kriging; Statistical physics; Computer science; Physics; Geometry; Spatial variability","score_opus":0.01416797251932832,"score_gpt":0.2490305476955081,"score_spread":0.23486257517617976,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2048676560","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.37167132,0.00020279443,0.03869535,0.0002704732,0.00004109313,0.00004724735,0.000004698644,0.0003418044,0.5887252],"genre_scores_gemma":[0.973244,0.000005066081,0.0068573034,0.00009160373,0.00018235188,0.000019736783,0.000031125408,0.000021824299,0.019546948],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99875,0.00001151746,0.00032899954,0.0002855214,0.00016120133,0.0004627878],"domain_scores_gemma":[0.9992706,0.00021741526,0.00007415867,0.00031915942,0.00004113608,0.00007754098],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.000063211206,0.00018554734,0.00038272844,0.00010200512,0.00006559014,0.000024404208,0.00022744067,0.0002174572,0.016744182],"category_scores_gemma":[0.00007885469,0.00016071039,0.00013655033,0.00036662706,0.00017054754,0.00004795665,0.00006624902,0.00023600881,0.00042210057],"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":[0.000062716936,0.0015046436,0.0069778007,0.000299623,0.0002602492,0.0001232642,0.00016299353,0.0008202728,0.03346824,0.94265664,0.013201341,0.0004622248],"study_design_scores_gemma":[0.00047343053,0.000034085828,0.00025706357,0.000009528083,0.00018214127,0.00012572149,0.00009769947,0.029654786,0.057872634,0.9100873,0.0008757327,0.00032989142],"about_ca_topic_score_codex":0.00012081265,"about_ca_topic_score_gemma":0.0000143307125,"teacher_disagreement_score":0.60157275,"about_ca_system_score_codex":0.00004353399,"about_ca_system_score_gemma":0.000020364832,"threshold_uncertainty_score":0.98415464},"labels":[],"label_agreement":null},{"id":"W2050228971","doi":"10.1023/b:matg.0000037736.00489.b5","title":"Indicator Simulation Accounting for Multiple-Point Statistics","year":2004,"lang":"en","type":"article","venue":"Mathematical Geology","topic":"Soil Geostatistics and Mapping","field":"Environmental Science","cited_by":63,"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":"Universidad de Chile","keywords":"Variogram; Statistics; Geostatistics; Kriging; Computer science; Range (aeronautics); Data mining; Independence (probability theory); Point (geometry); Mathematics; Spatial variability; Engineering","score_opus":0.016888280941748626,"score_gpt":0.2684607185321545,"score_spread":0.2515724375904059,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2050228971","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0854237,0.0000032900716,0.91221297,0.00023256023,0.00007094881,0.0003074097,0.000022388384,0.00004043939,0.0016862693],"genre_scores_gemma":[0.78340775,6.7843035e-7,0.21613485,0.00027280799,0.000031768825,0.000040648363,0.00001882375,0.0000120411505,0.000080670856],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99907875,0.000012718024,0.0002631163,0.00021242695,0.00013677686,0.00029621934],"domain_scores_gemma":[0.9988885,0.00078716606,0.00009318844,0.000146848,0.000011749644,0.00007255318],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00022611741,0.000103659455,0.00015988383,0.000025294845,0.0001108987,0.000017811506,0.0001152218,0.0000765623,0.0013554165],"category_scores_gemma":[0.0011222274,0.00009415627,0.000030145658,0.00006181212,0.00015766041,0.00005277605,0.000111177826,0.0000724196,0.0011707013],"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":[0.00009263289,0.00072404055,0.043473933,0.00035163606,0.00007339915,0.00003521634,0.0030820991,0.29164985,0.002061446,0.6236409,0.0029470955,0.03186776],"study_design_scores_gemma":[0.00093180407,0.000093584174,0.015760753,0.000012150776,0.000022928143,0.000007239117,0.00008048849,0.24063788,0.00015597157,0.7392141,0.0028815165,0.00020156498],"about_ca_topic_score_codex":0.000035289635,"about_ca_topic_score_gemma":0.000024625155,"teacher_disagreement_score":0.69798404,"about_ca_system_score_codex":0.000067882975,"about_ca_system_score_gemma":0.000010267934,"threshold_uncertainty_score":0.999607},"labels":[],"label_agreement":null},{"id":"W2056832631","doi":"10.1007/s11004-005-8751-z","title":"Book Review: Geodynamics By D. L. Turcotte and G. Schubert, Cambridge University Press, New York, 2002, 456 p., U.S.$ 110 (hb), $45 (pb) ISBN 0-521-66186-2, 0-521-66624-4.","year":2005,"lang":"en","type":"article","venue":"Mathematical Geology","topic":"Geological Modeling and Analysis","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":"Carleton University","funders":"","keywords":"Geodynamics; Geology; Hydrogeology; Geotechnical engineering; Seismology","score_opus":0.010628665788660122,"score_gpt":0.1923604020888941,"score_spread":0.18173173630023398,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2056832631","genre_codex":"review","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"review","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.04012763,0.7492132,0.026126144,0.069739036,0.0003337333,0.001305372,0.0002958075,0.0006246163,0.11223443],"genre_scores_gemma":[0.059467643,0.12192623,0.024239069,0.047622968,0.0008489418,0.0000063667044,0.00071660616,0.000049977556,0.7451222],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9975193,0.00019848783,0.0005287989,0.0006888788,0.00031665617,0.00074783585],"domain_scores_gemma":[0.9984244,0.00032408914,0.00017484202,0.00048734373,0.00006348907,0.00052583107],"candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0004505994,0.00036875615,0.00079854194,0.00008277833,0.00022395274,0.000050706418,0.00049342774,0.00031687637,0.009551701],"category_scores_gemma":[0.00021168224,0.00029352945,0.00019036746,0.00023703543,0.00034430492,0.00021076534,0.00009990649,0.00045913848,0.0016200078],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00003594117,0.000096218835,0.0024037554,0.00026870586,0.00009327254,0.000034969355,0.000034971014,0.0012861216,0.000008658122,0.0019228957,0.9854688,0.00834568],"study_design_scores_gemma":[0.00043949293,0.00012507322,0.0011339609,0.00013167258,0.00022786594,0.00008247015,0.000023252678,0.13809527,0.000009407794,0.00043591112,0.858886,0.0004096103],"about_ca_topic_score_codex":0.0013551,"about_ca_topic_score_gemma":0.00023338084,"teacher_disagreement_score":0.6328878,"about_ca_system_score_codex":0.000012432952,"about_ca_system_score_gemma":0.00005157181,"threshold_uncertainty_score":0.99995166},"labels":[],"label_agreement":null},{"id":"W2059380019","doi":"10.1007/s11004-005-1558-0","title":"Assessing the Goodness-of-Fit of Statistical Distributions When Data Are Grouped","year":2005,"lang":"en","type":"article","venue":"Mathematical Geology","topic":"Soil Geostatistics and Mapping","field":"Environmental Science","cited_by":14,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"BC Cancer Agency","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Goodness of fit; Statistics; Test statistic; Statistic; Statistical hypothesis testing; Anderson–Darling test; Mathematics; Pearson's chi-squared test; Computer science; Econometrics","score_opus":0.07815415372851857,"score_gpt":0.33971635749681295,"score_spread":0.26156220376829437,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2059380019","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.15049581,0.000028371203,0.8365834,0.0022758362,0.00006444752,0.0001940774,0.0002687187,0.00002148676,0.010067876],"genre_scores_gemma":[0.934918,0.000002662358,0.06479793,0.00007553946,0.000026595015,0.000007248213,0.000060812097,0.0000063014013,0.000104913765],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9989001,0.00007735615,0.0003783589,0.00021004525,0.0002058923,0.0002282043],"domain_scores_gemma":[0.99827,0.000913379,0.00015885616,0.00058506225,0.000014278605,0.000058467198],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00043866405,0.00009143136,0.00023921292,0.000012470231,0.000082341496,0.000016131222,0.00049375277,0.00005761242,0.0037278],"category_scores_gemma":[0.00093585515,0.00006245868,0.000023776298,0.00009174778,0.00074291177,0.000111172805,0.00066017924,0.000113557646,0.00019262562],"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":[0.000015746604,0.001129763,0.059860162,0.00022770037,0.00009367005,0.00001905618,0.0011496088,0.00045956756,0.0011202866,0.8815666,0.017589988,0.03676788],"study_design_scores_gemma":[0.0005219071,0.00008269136,0.32117447,0.00007077924,0.00016016926,0.000051654166,0.0009587462,0.1439405,0.00027979232,0.5209703,0.011483219,0.0003057744],"about_ca_topic_score_codex":0.00009421297,"about_ca_topic_score_gemma":0.000062652805,"teacher_disagreement_score":0.78442216,"about_ca_system_score_codex":0.000021810314,"about_ca_system_score_gemma":0.0000117076825,"threshold_uncertainty_score":0.9971829},"labels":[],"label_agreement":null},{"id":"W2060388003","doi":"10.1023/b:matg.0000028440.29965.2d","title":"Fitting the Linear Model of Coregionalization by Generalized Least Squares","year":2004,"lang":"en","type":"article","venue":"Mathematical Geology","topic":"Soil Geostatistics and Mapping","field":"Environmental Science","cited_by":40,"is_retracted":false,"has_abstract":false,"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":"Mathematics; Variogram; Statistics; Least-squares function approximation; Non-linear least squares; Estimator; Sill; Ordinary least squares; Context (archaeology); Covariance; Generalized least squares; Monte Carlo method; Applied mathematics; Kriging; Geology","score_opus":0.021623228988447027,"score_gpt":0.24482902821479618,"score_spread":0.22320579922634914,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2060388003","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.34810632,0.000019698076,0.64554393,0.0012889788,0.000023129875,0.00012231266,0.0000059680633,0.000017950651,0.004871733],"genre_scores_gemma":[0.97066164,0.0000070485894,0.02827472,0.00046564042,0.000014590365,0.000013897647,0.000011936428,0.0000081736425,0.00054233905],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.999356,0.00002355367,0.00020380261,0.00012058936,0.00014537961,0.00015071357],"domain_scores_gemma":[0.9996447,0.00010009572,0.00007524996,0.00013751686,0.000009813531,0.00003265663],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00015087595,0.000069007765,0.00012076755,0.000008841176,0.000069060516,0.0000044077738,0.00013435067,0.000045697747,0.00052564126],"category_scores_gemma":[0.0001571324,0.000046655594,0.000029821067,0.000070365546,0.00028968087,0.000023058425,0.00010123904,0.0000529367,0.00012186789],"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":[0.000015394495,0.0001888827,0.0020847695,0.000047742567,0.000018849742,0.0000021315916,0.0015261816,0.35349303,0.0087825395,0.62922966,0.0034706092,0.0011401811],"study_design_scores_gemma":[0.00035044894,0.000032890446,0.00039793682,0.000012082356,0.0000130480585,0.000007670622,0.000067956775,0.5297762,0.00077166175,0.46802843,0.00045566104,0.00008603264],"about_ca_topic_score_codex":0.00010217238,"about_ca_topic_score_gemma":0.000012529496,"teacher_disagreement_score":0.6225553,"about_ca_system_score_codex":0.0000190264,"about_ca_system_score_gemma":0.000007474016,"threshold_uncertainty_score":0.5755403},"labels":[],"label_agreement":null},{"id":"W2087028304","doi":"10.1007/s11004-005-5951-5","title":"Fractal Analysis of the Gray-Scale Intensity Data of Finely Laminated Sediments from Bainbridge Crater Lake, Galápagos","year":2005,"lang":"en","type":"article","venue":"Mathematical Geology","topic":"Geology and Paleoclimatology Research","field":"Earth and Planetary Sciences","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 Manitoba","funders":"","keywords":"Geology; Impact crater; Volcano; Fractal dimension; Hurst exponent; Maar; Radiocarbon dating; Fractal; Fractal analysis; Geomorphology; Paleontology; Physics","score_opus":0.035927023053823684,"score_gpt":0.2699684897415196,"score_spread":0.23404146668769593,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2087028304","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.9938178,0.000075522075,0.0003343119,0.0013028694,0.00008002792,0.00012838891,0.0003995932,0.0000120720615,0.0038494328],"genre_scores_gemma":[0.9976821,0.0000056292756,0.0010305659,0.00022729475,0.000022563256,9.4002377e-7,0.00066950184,0.0000021283784,0.0003592596],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.9984035,0.0002741713,0.00045134436,0.00031604158,0.0002254288,0.00032953866],"domain_scores_gemma":[0.99804574,0.0008234648,0.0001597315,0.0007984857,0.000099863035,0.000072705865],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0005608209,0.00013126108,0.0006056096,0.00013100945,0.00007352695,0.0000051673273,0.0008362033,0.00021260101,0.019314261],"category_scores_gemma":[0.00031909771,0.000081336526,0.000113700255,0.0004635647,0.00081621733,0.00008234427,0.00020318184,0.0002741921,0.0003316246],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000079538826,0.00009988144,0.9982666,0.00001779312,0.00040284835,0.000006707487,0.00019984762,0.00017741756,0.00003073533,0.00006354765,0.00037886563,0.0002762113],"study_design_scores_gemma":[0.00023272302,0.00004655857,0.92495596,0.000008305135,0.00032240036,0.000011664357,0.00005011027,0.071523204,0.00047885708,0.002113669,0.00017961976,0.00007692744],"about_ca_topic_score_codex":0.00022384468,"about_ca_topic_score_gemma":0.01241836,"teacher_disagreement_score":0.07331064,"about_ca_system_score_codex":6.917443e-7,"about_ca_system_score_gemma":0.000031149244,"threshold_uncertainty_score":0.9815822},"labels":[],"label_agreement":null},{"id":"W2094388921","doi":"10.1023/b:matg.0000041181.32596.5d","title":"Multifractality as a Measure of Spatial Distribution of Geochemical Patterns","year":2004,"lang":"en","type":"article","venue":"Mathematical Geology","topic":"Geochemistry and Geologic Mapping","field":"Computer Science","cited_by":45,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Multifractal system; Fractal dimension; Exponent; Fractal; Box counting; Dispersion (optics); Measure (data warehouse); Mineralogy; Geology; Fractal analysis; Mathematics; Physics; Mathematical analysis; Optics","score_opus":0.014055280218735137,"score_gpt":0.24053519273466592,"score_spread":0.22647991251593078,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2094388921","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.46599317,0.0000077109,0.5301566,0.0014726318,0.000034604116,0.00007826065,0.000005749623,0.00003059679,0.0022206365],"genre_scores_gemma":[0.9950576,9.592795e-7,0.004809262,0.00003849485,0.00002105939,0.0000090447065,0.0000173361,0.0000014807828,0.000044750042],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9987968,0.000048499463,0.00042538744,0.0002589371,0.00022714977,0.00024319686],"domain_scores_gemma":[0.9989413,0.00016217321,0.00018051361,0.00045883056,0.00018386095,0.000073340554],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00031467393,0.000119837605,0.00033456,0.000019467985,0.000026774578,0.0000057416746,0.00047729284,0.00017705641,0.00015920456],"category_scores_gemma":[0.0010817829,0.00010222588,0.00010232486,0.00010972705,0.0001988137,0.000055014396,0.00027434275,0.00014723341,0.000034288187],"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":[0.00006537245,0.0016930765,0.012014052,0.0010418915,0.00010048217,0.000059279464,0.001397202,0.0004914513,0.054165695,0.922219,0.00005957591,0.0066929297],"study_design_scores_gemma":[0.0009674469,0.00019951958,0.015040998,0.00012365537,0.000020892556,0.00014076289,0.000054816297,0.006380928,0.2606983,0.71593213,0.00021590694,0.00022462821],"about_ca_topic_score_codex":0.00016514037,"about_ca_topic_score_gemma":0.0000051841434,"teacher_disagreement_score":0.5290644,"about_ca_system_score_codex":0.000019857433,"about_ca_system_score_gemma":0.000056915174,"threshold_uncertainty_score":0.41686505},"labels":[],"label_agreement":null},{"id":"W2095013921","doi":"10.1023/b:matg.0000028438.48852.b0","title":"Transformation of Residuals to Avoid Artifacts in Geostatistical Modelling with a Trend","year":2004,"lang":"en","type":"article","venue":"Mathematical Geology","topic":"Soil Geostatistics and Mapping","field":"Environmental Science","cited_by":29,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Alberta","funders":"University of Alberta","keywords":"Residual; Transformation (genetics); Variable (mathematics); Robustness (evolution); Mathematics; Range (aeronautics); Statistics; Econometrics; Applied mathematics; Computer science; Algorithm","score_opus":0.017963280751917603,"score_gpt":0.2426824495796999,"score_spread":0.22471916882778228,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2095013921","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.4748774,0.000001729184,0.51466113,0.00044872964,0.0000071809836,0.00014527886,0.0000045456677,0.000009032129,0.009844972],"genre_scores_gemma":[0.8874085,0.000001548385,0.11238904,0.000117255295,0.0000038767043,0.000020143414,0.000005184741,0.0000070404794,0.000047426613],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9990086,0.00002621168,0.00033228422,0.0001721094,0.0001902426,0.0002705416],"domain_scores_gemma":[0.9995707,0.00015657609,0.000042275944,0.00012796224,0.000006126021,0.000096360935],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00021807787,0.00009755125,0.00021829676,0.00005996872,0.00002658915,0.0000063662205,0.00008691859,0.000054260152,0.00046815778],"category_scores_gemma":[0.000062675885,0.00007827362,0.00001616691,0.0001952559,0.00014559811,0.000053952263,0.000037633286,0.0000876236,0.00025645446],"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":[0.00011423384,0.0002968626,0.0013304569,0.00012346411,0.0000109027105,0.00004248386,0.007960666,0.4979983,0.00077359885,0.48793116,0.00003852585,0.00337935],"study_design_scores_gemma":[0.0016310312,0.0006221973,0.015492397,0.00018954351,0.00002781943,0.000057045065,0.0005510256,0.044457868,0.002160915,0.9340664,0.0003897548,0.00035397767],"about_ca_topic_score_codex":0.0002590749,"about_ca_topic_score_gemma":0.0005385893,"teacher_disagreement_score":0.4535404,"about_ca_system_score_codex":0.00004523179,"about_ca_system_score_gemma":0.00001103768,"threshold_uncertainty_score":0.51259995},"labels":[],"label_agreement":null},{"id":"W2104583144","doi":"10.1007/s11004-005-9025-5","title":"Semivariogram Models Based on Geometric Offsets","year":2006,"lang":"en","type":"article","venue":"Mathematical Geology","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":"Variogram; Kriging; Geostatistics; Gaussian; Mathematics; Gaussian network model; Statistics; Hydrogeology; Computer science; Geology; Geotechnical engineering; Spatial variability","score_opus":0.0129465720165296,"score_gpt":0.2216201547770215,"score_spread":0.2086735827604919,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2104583144","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.08061148,0.000008865228,0.4961641,0.00056653103,0.00007550816,0.00019636493,0.0000052492214,0.00008949887,0.4222824],"genre_scores_gemma":[0.97651625,7.190749e-7,0.021235986,0.00057002733,0.000025724288,0.000024388268,0.000012985198,0.00001098563,0.0016029419],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99895805,0.000029179262,0.00021072172,0.00024436024,0.00023329846,0.00032441565],"domain_scores_gemma":[0.9992953,0.00033833753,0.000047451573,0.00024403306,0.0000062487134,0.00006861581],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00018750616,0.00011818699,0.00016985105,0.00008938752,0.00006824714,0.000015252216,0.00014887736,0.000086862856,0.0051000533],"category_scores_gemma":[0.00010005005,0.00009930078,0.000048587466,0.00035233487,0.00015452631,0.000030693212,0.00009065283,0.000102971164,0.0017766228],"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":[0.000051232506,0.0020417299,0.025376003,0.00008830355,0.000022601293,0.00015177611,0.000116243,0.34022784,0.00026277642,0.5419774,0.064992435,0.02469164],"study_design_scores_gemma":[0.00020971427,0.00007006266,0.011643675,0.0000056308504,0.000007717567,0.000005851797,0.0000038210965,0.5431058,0.00004014582,0.4425148,0.0022739593,0.00011881617],"about_ca_topic_score_codex":0.0003223763,"about_ca_topic_score_gemma":0.000021122944,"teacher_disagreement_score":0.8959048,"about_ca_system_score_codex":0.000041647265,"about_ca_system_score_gemma":0.000005016404,"threshold_uncertainty_score":0.9990006},"labels":[],"label_agreement":null},{"id":"W2106308596","doi":"10.1023/a:1007570402430","title":"Geostatistical Simulation of Regionalized Pore-Size Distributions Using Min/Max Autocorrelation Factors","year":2000,"lang":"en","type":"article","venue":"Mathematical Geology","topic":"Soil Geostatistics and Mapping","field":"Environmental Science","cited_by":130,"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","funders":"","keywords":"Autocorrelation; Mathematics; Parametric statistics; Statistics; Geostatistics; Spatial correlation; Series (stratigraphy); Statistical physics; Applied mathematics; Spatial variability; Geology; Physics","score_opus":0.025824805177982166,"score_gpt":0.2823065324349262,"score_spread":0.256481727256944,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2106308596","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.56557494,0.000003865278,0.42924288,0.00009056316,0.000037391186,0.00020640765,0.0000359687,0.00002925026,0.0047786967],"genre_scores_gemma":[0.96980333,0.0000015456556,0.029298723,0.000038142567,0.00001433175,0.000008536111,0.00009319895,0.000010155944,0.00073206006],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99877363,0.00007161467,0.0004300886,0.00022605345,0.00023392928,0.00026467547],"domain_scores_gemma":[0.99841344,0.001171523,0.000108989494,0.00019159194,0.000019040943,0.00009539859],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00015770478,0.00013238158,0.0002526064,0.000021347416,0.00010989261,0.000009098399,0.000103792794,0.00011722381,0.023737187],"category_scores_gemma":[0.0007453789,0.000117292264,0.00006036345,0.00016929752,0.00039773015,0.000066234315,0.000058926595,0.00009861084,0.00027084953],"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":[0.00026398143,0.00143608,0.10413026,0.00021552155,0.00014696576,0.00007204641,0.0028006204,0.40361583,0.001999758,0.4526734,0.0023273937,0.030318145],"study_design_scores_gemma":[0.00033578297,0.000051212897,0.064997025,0.000017604067,0.00004653698,0.000014703368,0.0000312771,0.75565237,0.000039307193,0.1768532,0.0018045426,0.00015643881],"about_ca_topic_score_codex":0.00015464352,"about_ca_topic_score_gemma":0.000007779678,"teacher_disagreement_score":0.40422833,"about_ca_system_score_codex":0.00006817484,"about_ca_system_score_gemma":0.00001327668,"threshold_uncertainty_score":0.97715527},"labels":[],"label_agreement":null},{"id":"W2111521506","doi":"10.1023/b:matg.0000028441.62108.8a","title":"A New Model for Quantifying Anisotropic Scale Invariance and for Decomposition of Mixing Patterns","year":2004,"lang":"en","type":"article","venue":"Mathematical Geology","topic":"Geochemistry and Geologic Mapping","field":"Computer Science","cited_by":94,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"York University","funders":"","keywords":"Scale invariance; Isotropy; Scaling; Rotational invariance; Statistical physics; Spectral density; Field (mathematics); Power law; Mixing (physics); Mathematical analysis; Mathematics; Scale (ratio); Function (biology); Physics; Geometry; Algorithm; Statistics; Optics; Quantum mechanics; Pure mathematics","score_opus":0.05030697248293809,"score_gpt":0.301086942264754,"score_spread":0.25077996978181594,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2111521506","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.063146055,0.000021967648,0.93346334,0.0028624705,0.000031150255,0.00023375102,0.0000020995678,0.00003110445,0.0002080739],"genre_scores_gemma":[0.53785914,0.0000012035916,0.46191508,0.00006848372,0.000014515453,0.000024616047,0.0000016739662,0.0000015138535,0.00011380966],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99925864,0.000009271311,0.00022646069,0.000238928,0.000052322055,0.0002143793],"domain_scores_gemma":[0.99940753,0.00020154694,0.00008353701,0.0001907021,0.000059400045,0.00005725828],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00014665455,0.0000876804,0.00021298158,0.00002633961,0.000067890935,0.000018687117,0.00022260557,0.00008334458,0.0000070896153],"category_scores_gemma":[0.00011638976,0.000080796504,0.00004916695,0.000048298494,0.00003868342,0.00008171127,0.00011192206,0.000043789725,0.0000016471381],"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":[0.00001991055,0.00007964195,0.0005614857,0.00083646795,0.000017095574,0.0000014342453,0.0013099463,0.0062623285,0.011188386,0.9770928,0.000045455796,0.0025850355],"study_design_scores_gemma":[0.000496874,0.000062824394,0.00014087286,0.00004797792,0.000006509603,0.000019409732,0.000015052996,0.42608723,0.0056475354,0.56738776,0.000024124854,0.000063815365],"about_ca_topic_score_codex":0.000007920547,"about_ca_topic_score_gemma":0.000008540942,"teacher_disagreement_score":0.47471306,"about_ca_system_score_codex":0.000009177671,"about_ca_system_score_gemma":0.00003711107,"threshold_uncertainty_score":0.32947856},"labels":[],"label_agreement":null},{"id":"W2114913871","doi":"10.1023/b:matg.0000041179.79093.87","title":"Identification of Mineral Grains in a Petrographic Thin Section Using Phi- and Max-Images","year":2004,"lang":"en","type":"article","venue":"Mathematical Geology","topic":"Medical Image Segmentation Techniques","field":"Computer Science","cited_by":15,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"Brock University","keywords":"Petrography; Thin section; Edge detection; Artificial intelligence; Rotation (mathematics); Geology; Image segmentation; Segmentation; Image (mathematics); Polarizer; Computer vision; Birefringence; Image processing; Computer science; Mineralogy; Mathematics; Optics; Physics","score_opus":0.01866829887877061,"score_gpt":0.292760868058199,"score_spread":0.27409256917942837,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2114913871","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.30544895,0.000021363068,0.6937754,0.00046627055,0.000039247134,0.00010972613,3.1622386e-7,0.000053170777,0.00008552842],"genre_scores_gemma":[0.76958287,0.000007766156,0.23023501,0.00011712311,0.000014251491,0.000014018862,9.0552896e-7,0.0000038050835,0.000024233053],"study_design_codex":"bench_or_experimental","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99902916,0.000070473136,0.00038954054,0.00020800471,0.0001573916,0.00014545125],"domain_scores_gemma":[0.9994888,0.00010461943,0.000116382056,0.00020325126,0.000042159878,0.000044788827],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00046901553,0.00007536494,0.00017493682,0.0002368592,0.00002590224,0.000025565849,0.0001863947,0.00007210191,0.000017936381],"category_scores_gemma":[0.00028360286,0.00006834726,0.000028542314,0.00033257026,0.0002196658,0.00020671196,0.000095842304,0.00010616694,0.0000037287252],"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":[0.000016139124,0.00096937164,0.005344424,0.0005978703,0.00003857435,0.00006691417,0.0056527574,0.00029943284,0.55385727,0.41871768,0.00011694746,0.014322626],"study_design_scores_gemma":[0.00095567387,0.00019640519,0.014128236,0.00010300408,0.000015353724,0.00019048742,0.00016564359,0.07044439,0.080191016,0.83338964,0.0000050381936,0.00021508751],"about_ca_topic_score_codex":0.000045631667,"about_ca_topic_score_gemma":0.000012045613,"teacher_disagreement_score":0.47366622,"about_ca_system_score_codex":0.000023303224,"about_ca_system_score_gemma":0.000019858151,"threshold_uncertainty_score":0.27871203},"labels":[],"label_agreement":null},{"id":"W2119509409","doi":"10.1023/a:1007525900030","title":"Elicited Data and Incorporation of Expert Opinion for Statistical Inference in Spatial Studies","year":2000,"lang":"en","type":"article","venue":"Mathematical Geology","topic":"Statistical Methods and Bayesian Inference","field":"Mathematics","cited_by":19,"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":"Computer science; Inference; Prior probability; Bayesian inference; Machine learning; Artificial intelligence; Bayesian probability; Realization (probability); Statistical inference; Expert elicitation; Field (mathematics); Feature (linguistics); Construct (python library); Data mining; Data science; Statistics; Mathematics","score_opus":0.21485939415848318,"score_gpt":0.48061142121970524,"score_spread":0.26575202706122203,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2119509409","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.015581594,0.00010837269,0.9830277,0.0003468932,0.000050655864,0.00040792016,0.00011026865,0.000021942997,0.00034466933],"genre_scores_gemma":[0.2000366,0.00014667869,0.79956573,0.0000647934,0.000047128386,0.00006585805,0.00004100252,0.000011928217,0.000020309792],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99843866,0.00018383174,0.0006739873,0.00032924747,0.00014087866,0.00023340202],"domain_scores_gemma":[0.98863345,0.010713922,0.00011087942,0.000390152,0.00008983084,0.0000617521],"candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0007092381,0.0001505989,0.00058504223,0.00006983696,0.00003484272,0.000010643991,0.00020806592,0.00011893657,0.00054486183],"category_scores_gemma":[0.011492089,0.000119720215,0.000016860131,0.00010239496,0.0003999846,0.00007117899,0.0001403591,0.000107261214,0.000008574703],"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":[0.000101406695,0.00018874384,0.0005123272,0.00044984778,0.000020388658,0.000002869535,0.0006031247,6.774796e-7,0.000078797086,0.87560064,0.00026489052,0.12217629],"study_design_scores_gemma":[0.0005241356,0.0002255522,0.00096512755,0.00010614258,0.000013441745,0.0000053196836,0.00012398211,0.047955822,0.000068901696,0.9497541,0.00013540259,0.000122067795],"about_ca_topic_score_codex":0.000037954454,"about_ca_topic_score_gemma":0.000046160414,"teacher_disagreement_score":0.18445499,"about_ca_system_score_codex":0.000013367392,"about_ca_system_score_gemma":0.00003314135,"threshold_uncertainty_score":0.9968345},"labels":[],"label_agreement":null},{"id":"W2138946060","doi":"10.1023/b:matg.0000037737.11615.df","title":"Generalized Sequential Gaussian Simulation on Group Size ν and Screen-Effect Approximations for Large Field Simulations","year":2004,"lang":"en","type":"article","venue":"Mathematical Geology","topic":"Geological Modeling and Analysis","field":"Earth and Planetary Sciences","cited_by":99,"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":"Gaussian; Node (physics); Mathematics; Algorithm; Gaussian process; Ergodic theory; Gaussian random field; Applied mathematics; Mathematical optimization; Computer science; Mathematical analysis; Physics","score_opus":0.026939619447880096,"score_gpt":0.2785485208944647,"score_spread":0.2516089014465846,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2138946060","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.51987886,0.000025526582,0.47690582,0.0018982207,0.000044468536,0.00030742964,0.000051879077,0.000054575525,0.0008332244],"genre_scores_gemma":[0.98025906,0.000002172351,0.018691868,0.00065709115,0.00008951277,0.0000073592973,0.00016502748,0.0000031906663,0.00012469999],"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.9990186,0.00007974519,0.00024646398,0.00025738758,0.00011510078,0.00028269854],"domain_scores_gemma":[0.99793667,0.0017386987,0.000055241126,0.00014367522,0.000027366003,0.000098381206],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002632085,0.00013070898,0.00025963775,0.00006140499,0.00024582032,0.000033406664,0.00008195366,0.00014591124,0.0018971054],"category_scores_gemma":[0.00081486255,0.00009293843,0.000092937385,0.00011370322,0.000044823126,0.00005626574,0.000012109668,0.00010112577,0.000102214195],"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":[0.0001036725,0.000103597755,0.006703649,0.00005975453,0.000049342932,0.0000032386813,0.000107101405,0.89649343,0.000027359069,0.09350192,0.000020258125,0.0028266949],"study_design_scores_gemma":[0.0008968425,0.00041740938,0.0035385345,0.000010396835,0.000048297938,0.0000026078887,0.000009450255,0.7976094,0.000019409032,0.19710162,0.00023510812,0.00011093068],"about_ca_topic_score_codex":0.000109663255,"about_ca_topic_score_gemma":0.00036561012,"teacher_disagreement_score":0.46038023,"about_ca_system_score_codex":0.0000030805834,"about_ca_system_score_gemma":0.000007865862,"threshold_uncertainty_score":0.9990153},"labels":[],"label_agreement":null},{"id":"W2147863855","doi":"10.1023/a:1016094928524","title":"Statistical Evaluation of Compositional Differences Between Upper Eocene Impact Ejecta Layers","year":2002,"lang":"en","type":"article","venue":"Mathematical Geology","topic":"Geochemistry and Geologic Mapping","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":true,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of New Brunswick","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Geology","score_opus":0.06403180631107766,"score_gpt":0.30542950122719015,"score_spread":0.2413976949161125,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2147863855","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6080099,0.00005819505,0.35644332,0.0028238273,0.000058627076,0.00018520353,0.000015582193,0.000061994644,0.03234336],"genre_scores_gemma":[0.98165184,0.0000014209139,0.018084578,0.000042664382,0.000040648323,0.000014479793,0.000012906296,0.0000018007108,0.00014964388],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.99842054,0.00020298517,0.00034714938,0.00027385837,0.00046332704,0.00029212423],"domain_scores_gemma":[0.99845904,0.00081670575,0.000106317275,0.00030945914,0.0002095123,0.00009893635],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00059185026,0.00013560902,0.00032985496,0.0000551003,0.0000630146,0.000020834792,0.00042947382,0.00011654001,0.0054614376],"category_scores_gemma":[0.0005258722,0.00010364712,0.000072630035,0.00014997605,0.00021753114,0.000076788776,0.0001609313,0.00013398103,0.00017209548],"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":[0.000015720043,0.00092343194,0.18088926,0.0002583384,0.0003064668,0.00002182152,0.0015237444,0.0007433558,0.002024189,0.7891589,0.0037040256,0.020430775],"study_design_scores_gemma":[0.00044207086,0.00017649833,0.15370129,0.000023736637,0.000048220314,0.000046090954,0.000020254613,0.35436496,0.00066366163,0.4902929,0.000049585506,0.00017071485],"about_ca_topic_score_codex":0.0000064892056,"about_ca_topic_score_gemma":3.535647e-7,"teacher_disagreement_score":0.37364197,"about_ca_system_score_codex":0.000026127784,"about_ca_system_score_gemma":0.000030186746,"threshold_uncertainty_score":0.9954477},"labels":[],"label_agreement":null},{"id":"W24863145","doi":"10.1023/a:1023231404211","title":"A Simple Approach to Account for Radial Flow and Boundary Conditions When Kriging Hydraulic Head Fields for Confined Aquifers","year":2003,"lang":"en","type":"article","venue":"Mathematical Geology","topic":"Groundwater flow and contamination studies","field":"Environmental Science","cited_by":29,"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":"Hydrogeology; Kriging; Hydraulic head; Aquifer; Inverse problem; Head (geology); Inverse; Geology; Applied mathematics; Finite element method; Boundary value problem; Mathematics; Mathematical analysis; Geometry; Geotechnical engineering; Groundwater; Statistics; Engineering","score_opus":0.022411582838830296,"score_gpt":0.26458116459200914,"score_spread":0.24216958175317885,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W24863145","genre_codex":"methods","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.17814833,0.000016582897,0.8098103,0.0011632852,0.000061909865,0.0008583203,0.000018453695,0.000029221192,0.009893642],"genre_scores_gemma":[0.96277136,8.263577e-7,0.031591706,0.0019930564,0.000032464224,0.00082717347,0.000031061776,0.000011481117,0.0027408549],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99913806,0.000028375262,0.00019430158,0.0002539719,0.00008376534,0.00030150704],"domain_scores_gemma":[0.99946326,0.00028745417,0.000028152714,0.00012136524,0.000013259714,0.0000864854],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002169856,0.000117439755,0.00022879624,0.000028970093,0.00025162683,0.000035813566,0.00008282928,0.00007181895,0.0007121154],"category_scores_gemma":[0.00017093141,0.00010081058,0.000050592545,0.0000462162,0.0001967169,0.00006236323,0.000056364315,0.000047463225,0.00006970621],"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":[0.00043537543,0.0018461124,0.017867202,0.00095339376,0.0005160628,0.0000100735315,0.02689255,0.0019076939,0.0034787355,0.65951234,0.24573798,0.04084244],"study_design_scores_gemma":[0.0027901402,0.00051734055,0.0048215124,0.000010208048,0.00010180892,0.00004834885,0.0012223945,0.03737296,0.00048221886,0.34158716,0.61052805,0.00051788444],"about_ca_topic_score_codex":0.000019092278,"about_ca_topic_score_gemma":0.00005868978,"teacher_disagreement_score":0.784623,"about_ca_system_score_codex":0.000028508024,"about_ca_system_score_gemma":0.000009460647,"threshold_uncertainty_score":0.77971643},"labels":[],"label_agreement":null},{"id":"W342191223","doi":"10.1023/a:1021312506179","title":"Oscillatory Zoning in an Agate from Kazakhstan: Autocorrelation Functions and Fractal Statistics of Trace Element Distributions","year":2002,"lang":"en","type":"article","venue":"Mathematical Geology","topic":"Mineralogy and Gemology Studies","field":"Earth and Planetary Sciences","cited_by":9,"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 Manitoba","funders":"","keywords":"Fractal; Trace element; Geometry; Autocorrelation; Mineralogy; Geology; Hurst exponent; TRACE (psycholinguistics); Scaling; Mathematics; Mathematical analysis; Statistics","score_opus":0.02103318824894891,"score_gpt":0.22871774261851016,"score_spread":0.20768455436956124,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W342191223","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"codex-gemma-dda1882f352a","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.96920526,0.00031529908,0.0273112,0.00033273938,0.00008702028,0.00011985983,0.00027893911,0.000015505373,0.0023341759],"genre_scores_gemma":[0.9953917,0.00001734765,0.004185456,0.000032594537,0.000020371874,0.0000031606517,0.00013297792,0.0000013981685,0.00021497103],"study_design_codex":"observational","study_design_gemma":"observational","domain_scores_codex":[0.99924207,0.000090855574,0.0002650978,0.00016018563,0.0000661432,0.0001756468],"domain_scores_gemma":[0.9992687,0.00049751095,0.00006480104,0.00009463236,0.000022564771,0.00005178076],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001395399,0.00008204366,0.00019716553,0.000048319383,0.000101855454,0.0000050618355,0.000047286478,0.00009313822,0.005612682],"category_scores_gemma":[0.000109841785,0.00007018356,0.000014545809,0.000073257754,0.00028265643,0.00007117622,0.0000117186,0.00013494086,0.000113373346],"study_design_candidate":"observational","study_design_consensus":"observational","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000016894044,0.00009998855,0.98112524,0.000017205462,0.000029963427,0.000016146636,0.0010155832,0.0007680077,0.000022205602,0.009908443,0.0005092263,0.0064711072],"study_design_scores_gemma":[0.00026784715,0.00017681994,0.8161709,0.000007789241,0.00002622393,0.000009276826,0.0002981306,0.1359369,0.0000034616444,0.046745233,0.00026952318,0.00008793238],"about_ca_topic_score_codex":0.00020240448,"about_ca_topic_score_gemma":0.002378643,"teacher_disagreement_score":0.16495436,"about_ca_system_score_codex":0.0000030134133,"about_ca_system_score_gemma":0.000005926168,"threshold_uncertainty_score":0.9952963},"labels":[],"label_agreement":null}]}