{"meta":{"page":1,"per_page":50,"max_per_page":100,"total":7,"total_is_capped":false,"direct_labels_cover":0,"predictions_cover":7,"direct_label_status":"direct model label, unvalidated","prediction_status":"machine_predicted_unvalidated (Codex and Gemma teacher distillation)","score_status":"score_only:v0-immature-baseline (scores rank; they never assert a category)","snapshot":{"source":"OpenAlex, pinned release, all 482 partitions","release":"2026-06-24","frame_built":"2026-07-12","author_layer_release":"2026-06-26"},"query_hash":"73c40d33cae1","filters":{"venue":"Demographic research monographs"}},"results":[{"id":"W55367362","doi":"10.1007/978-3-642-11520-2_4","title":"The emergence of supercentenarians in Canada","year":2010,"lang":"en","type":"book-chapter","venue":"Demographic research monographs","topic":"Insurance, Mortality, Demography, Risk Management","field":"Social Sciences","cited_by":14,"is_retracted":false,"has_abstract":false,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"Université de Montréal","funders":"","keywords":"Milestone; Demography; Suspect; Population; Geography; Genealogy; History; Political science; Cartography; Sociology; Law","authors":[{"name":"Bertrand Desjardins","is_ca":true},{"name":"Robert Bourbeau","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.06123072559590043,"gpt":0.34813502767278,"spread":0.2869043020768796,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006034721,0.0001938713,0.0003550398,0.002119167,0.0115886,0.003369687,0.00134131,0.000794554,0.01105311],"category_scores_gemma":[0.001959668,0.0003237509,0.0002869176,0.003968336,0.00285044,0.000876699,0.001876537,0.001603883,0.0005568572],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05574448,"about_ca_system_score_gemma":0.08003384,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9970492,"about_ca_topic_score_gemma":0.9991904,"domain_scores_codex":[0.9987687,0.00006078242,0.00001876606,0.0001297207,0.0002280779,0.0007937293],"domain_scores_gemma":[0.997959,0.0001483063,0.0001403307,0.0000680275,0.0008413167,0.0008429848],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0004537701,0.0001307181,0.2652725,0.0002164571,0.000081934,0.002568137,0.1039912,0.001155694,0.001726386,0.1980411,0.104461,0.3219012],"study_design_scores_gemma":[0.000032256,0.00006015357,0.4193469,0.0002495116,0.00003245766,0.0004947354,0.07022742,0.001648264,0.0005780531,0.003968656,0.5032543,0.0001073115],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8912832,0.006308897,0.0005681975,0.00921831,0.0002000037,0.00005797073,0.001395372,0.00008553747,0.09088261],"genre_scores_gemma":[0.9605731,0.002380917,0.0004486945,0.0008652579,0.00002469983,0.00001212655,0.0003501364,0.00003459609,0.03531039],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05574448,"threshold_uncertainty_score":0.4044564,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3111826016","doi":"10.1007/978-3-030-49970-9_9","title":"Supercentenarians and Semi-supercentenarians in France","year":2020,"lang":"en","type":"book-chapter","venue":"Demographic research monographs","topic":"Insurance, Mortality, Demography, Risk Management","field":"Social Sciences","cited_by":6,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"Université de Montréal","funders":"","keywords":"Life expectancy; Demography; Nominative case; Sample (material); Statistics; Geography; Genealogy; History; Computer science; Mathematics; Population; Artificial intelligence; Sociology","authors":[{"name":"Nadine Ouellette","is_ca":true},{"name":"France Meslé","is_ca":false},{"name":"Jacques Vallin","is_ca":false},{"name":"Jean‐Marie Robine","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.07751678691433608,"gpt":0.354177348710913,"spread":0.2766605617965769,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001487468,0.000251301,0.0002955066,0.002202539,0.000509797,0.0007164337,0.0004477224,0.0003970231,0.004478578],"category_scores_gemma":[0.004241027,0.000108457,0.0002676129,0.001315928,0.000393675,0.0003404242,0.0005976369,0.0002497842,0.0005755238],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001284187,"about_ca_system_score_gemma":0.0007863624,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1635961,"about_ca_topic_score_gemma":0.1584716,"domain_scores_codex":[0.9984834,0.0004900539,0.00008864295,0.0003468363,0.0002985042,0.000292617],"domain_scores_gemma":[0.9975364,0.0008857785,0.0007332647,0.0002120955,0.0005022186,0.0001303178],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001188242,0.0000198213,0.9598336,0.00005456734,0.00006166623,0.0004873628,0.004586604,0.000571834,0.0006279551,0.001234731,0.001912665,0.0304903],"study_design_scores_gemma":[0.000006404234,0.00006712582,0.9826826,0.00004404831,0.00001641137,0.0004278338,0.003496914,0.0008463851,0.0002846701,0.0002041571,0.01190804,0.0000154922],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9950002,0.0003808083,0.0003740383,0.0001643421,0.00001031216,0.000008909095,0.00166545,0.00001342036,0.002382644],"genre_scores_gemma":[0.9964134,0.0002186195,0.0002649438,0.00005790842,0.00001340769,0.00001191804,0.001648786,0.000006929141,0.001364053],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1635961,"threshold_uncertainty_score":0.3252877,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3110725171","doi":"10.1007/978-3-030-49970-9_2","title":"The International Database on Longevity: Data Resource Profile","year":2020,"lang":"en","type":"book-chapter","venue":"Demographic research monographs","topic":"Insurance, Mortality, Demography, Risk Management","field":"Social Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"","funders":"","keywords":"Longevity; Database; Population; Resource (disambiguation); Computer science; Demography; Geography; Medicine; Gerontology","authors":[{"name":"Dmitri A. Jdanov","is_ca":false},{"name":"Vladimir M. Shkolnikov","is_ca":false},{"name":"S. Gellers-Barkmann","is_ca":false}],"retraction":null,"screen_n_in":null,"score":{"opus":0.2294547381705192,"gpt":0.4179825232172756,"spread":0.1885277850467564,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006289633,0.001578183,0.003219969,0.01320633,0.0006416613,0.005648949,0.002379937,0.001835887,0.1422425],"category_scores_gemma":[0.04156169,0.001078045,0.001073323,0.03187279,0.000516135,0.003998164,0.003426709,0.002711393,0.1127576],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001951922,"about_ca_system_score_gemma":0.006224079,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004322689,"about_ca_topic_score_gemma":0.004024387,"domain_scores_codex":[0.9925891,0.001228656,0.003576948,0.0008382724,0.001358497,0.0004085055],"domain_scores_gemma":[0.9671618,0.01337883,0.005937131,0.005066977,0.006401901,0.002053476],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002523862,0.0000460934,0.00278819,0.007260893,0.00009613885,0.00009854334,0.0001961019,0.0004528111,0.0003637846,0.004450879,0.9517798,0.03221446],"study_design_scores_gemma":[0.0002816629,0.00003857624,0.01213214,0.002500795,0.00008207277,0.000236316,0.0001433625,0.0004059738,0.0004154621,0.004025213,0.979637,0.0001014871],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.000183014,0.0004200873,0.0008084622,0.0001685881,0.00003744636,0.0002455951,0.9950261,0.0009476281,0.002163112],"genre_scores_gemma":[0.00128333,0.001082831,0.002854808,0.0002263948,0.00006026217,0.001526495,0.9914712,0.0005038809,0.0009907673],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1422425,"threshold_uncertainty_score":0.4758485,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W3112942004","doi":"10.1007/978-3-030-49970-9_12","title":"Extreme Longevity in Quebec: Factors and Characteristics","year":2020,"lang":"en","type":"book-chapter","venue":"Demographic research monographs","topic":"Insurance, Mortality, Demography, Risk Management","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"Université de Montréal; Centre intégré de santé et de services sociaux de Chaudière-Appalaches; Centre Intégré de Santé et de Services Sociaux des Laurentides; Santé Montérégie","funders":"","keywords":"Centenarian; Census; Demography; Longevity; Population; Geography; Gerontology; Population ageing; Medicine; Sociology","authors":[{"name":"Mélissa Beaudry-Godin","is_ca":true},{"name":"Robert Bourbeau","is_ca":true},{"name":"Bertrand Desjardins","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.1438747186204614,"gpt":0.3591554379358223,"spread":0.2152807193153609,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005074658,0.0002504502,0.0002328313,0.001747939,0.002098247,0.001457785,0.0008378609,0.0003532335,0.005941452],"category_scores_gemma":[0.002094193,0.00009719378,0.0003480217,0.004850432,0.0006069922,0.0004357153,0.0005931787,0.000490682,0.000359715],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01689667,"about_ca_system_score_gemma":0.0109249,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9818158,"about_ca_topic_score_gemma":0.9871687,"domain_scores_codex":[0.9995379,0.00005848551,0.0000271149,0.00007808543,0.0001497825,0.0001485198],"domain_scores_gemma":[0.9975697,0.0001946606,0.0005973557,0.00007787639,0.001012937,0.000547375],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002835111,0.00002054481,0.9886646,0.0000261231,0.00004431501,0.000110878,0.0004995562,0.0002205467,0.000127624,0.0004642159,0.002788927,0.007004306],"study_design_scores_gemma":[0.000001524997,0.00001046203,0.9960046,0.00003038841,0.00001004869,0.00006204145,0.0006009882,0.0002398381,0.00002388027,0.00005728853,0.002951845,0.000006963142],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9699201,0.002318901,0.0003675495,0.001360998,0.00003215436,0.00007186664,0.01443448,0.00003624568,0.01145775],"genre_scores_gemma":[0.9946202,0.0005460788,0.0001495909,0.00009755637,0.0000126217,0.00002039725,0.002266088,0.000006448202,0.002280982],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01818419,"threshold_uncertainty_score":0.1225945,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2112723050","doi":"10.1007/978-3-319-65433-1_7","title":"Estimating the Goodman, Keyfitz and Pullum Kinship Equations: An Alternative Procedure","year":2017,"lang":"en","type":"book-chapter","venue":"Demographic research monographs","topic":"Insurance, Mortality, Demography, Risk Management","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Victoria","funders":"","keywords":"Kinship; Population; Applied mathematics; Fertility; Mathematics; Calculus (dental); Econometrics; Demography; Sociology; Anthropology","authors":[{"name":"Thomas K. Burch","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.1695742448272643,"gpt":0.4234555056846254,"spread":0.2538812608573611,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004189722,0.0008426118,0.001109739,0.002339133,0.0006016266,0.001824724,0.002639907,0.001477486,0.007503028],"category_scores_gemma":[0.01680259,0.0005690194,0.001336631,0.00216284,0.0007500134,0.002568452,0.001737371,0.002477681,0.001697697],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008248204,"about_ca_system_score_gemma":0.002028733,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007016675,"about_ca_topic_score_gemma":0.009893658,"domain_scores_codex":[0.9984797,0.0006403186,0.0001077538,0.0003581593,0.0003537855,0.0000603702],"domain_scores_gemma":[0.9971699,0.001966407,0.000134507,0.0003009905,0.000379628,0.00004847999],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000126834,0.0001745102,0.01000366,0.0003417304,0.0003845708,0.0003538085,0.001002566,0.08873629,0.003366457,0.39989,0.006470902,0.4891486],"study_design_scores_gemma":[0.00007631644,0.0001291887,0.005529654,0.0001208612,0.0001492095,0.0006078582,0.0002801279,0.623181,0.003356843,0.3408888,0.02555612,0.0001239724],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.007031175,0.0001630798,0.9905341,0.0002266952,0.00004230826,0.00006407296,0.0002036844,0.0001796671,0.001555245],"genre_scores_gemma":[0.06093195,0.0003268324,0.9319133,0.0001410838,0.00006713419,0.0002145555,0.000345033,0.0001006193,0.005959516],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007503028,"threshold_uncertainty_score":0.02510017,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W1919609713","doi":"10.1007/978-3-319-65433-1_9","title":"Cohort Component Projection: Algorithm, Technique, Model and Theory","year":2017,"lang":"en","type":"book-chapter","venue":"Demographic research monographs","topic":"demographic modeling and climate adaptation","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true},"ca_institutions":"University of Victoria","funders":"","keywords":"Projection (relational algebra); Component (thermodynamics); Population projection; Perspective (graphical); Population; Computer science; Cohort; Projections of population growth; Algorithm; Artificial intelligence; Statistics; Mathematics; Demography; Research methodology; Sociology","authors":[{"name":"Thomas K. Burch","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.2610728881257818,"gpt":0.4477922490320751,"spread":0.1867193609062933,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007064932,0.001234627,0.001328899,0.001468633,0.00107726,0.002409548,0.002556137,0.00118338,0.005290104],"category_scores_gemma":[0.01885385,0.0008203709,0.001276693,0.003579059,0.002083414,0.003586977,0.004748477,0.004567609,0.001895952],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001562079,"about_ca_system_score_gemma":0.00429058,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01237695,"about_ca_topic_score_gemma":0.006913971,"domain_scores_codex":[0.9975541,0.001412018,0.00008621904,0.000331979,0.0005083395,0.0001073343],"domain_scores_gemma":[0.9935407,0.004661416,0.000169491,0.000580714,0.0009053966,0.0001423119],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000110959,0.0000662591,0.003047898,0.0002133164,0.0001270763,0.000105038,0.0004440413,0.09032018,0.0003168324,0.6304847,0.02114519,0.2536184],"study_design_scores_gemma":[0.0000289644,0.00003612731,0.000484225,0.000105223,0.00003844559,0.0001643928,0.00008983306,0.4357674,0.0005937085,0.5431479,0.0194973,0.00004649965],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0006655846,0.0003836763,0.9970475,0.0003948517,0.00006474257,0.00004454608,0.0000817344,0.0001493312,0.001168075],"genre_scores_gemma":[0.05320024,0.002221499,0.9357897,0.000297298,0.000329218,0.0007737866,0.0008070484,0.0004066743,0.006174459],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01237695,"threshold_uncertainty_score":0.03736341,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null},{"id":"W2760874103","doi":"10.1007/978-3-319-65433-1_12","title":"Teaching the Fundamentals of Demography: A Model-Based Approach to Fertility","year":2017,"lang":"en","type":"book-chapter","venue":"Demographic research monographs","topic":"Complex Systems and Decision Making","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false},"ca_institutions":"University of Victoria","funders":"","keywords":"Fertility; Total fertility rate; Demography; Geography; Sociology; Population; Research methodology; Family planning","authors":[{"name":"Thomas K. Burch","is_ca":true}],"retraction":null,"screen_n_in":null,"score":{"opus":0.4086378109219296,"gpt":0.4781364606139662,"spread":0.06949864969203662,"validation_status":"score_only:v0-immature-baseline"},"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001083158,0.0007749256,0.0004735527,0.0007807193,0.0006581995,0.002181355,0.001405142,0.001223902,0.01537417],"category_scores_gemma":[0.002537667,0.0004171861,0.0006505219,0.001078122,0.001853503,0.002866357,0.001359197,0.003933727,0.005515848],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001711547,"about_ca_system_score_gemma":0.001278961,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002325193,"about_ca_topic_score_gemma":0.003712203,"domain_scores_codex":[0.9996874,0.000153343,0.00001383382,0.00004383459,0.00008342214,0.00001811667],"domain_scores_gemma":[0.9993033,0.0005360502,0.00002483246,0.00005447239,0.00005454277,0.00002684709],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00000335289,0.00002996798,0.0001687614,0.0001970042,0.000008695981,0.00005932693,0.0004914751,0.007762065,0.0001999118,0.8622146,0.05593609,0.0729287],"study_design_scores_gemma":[0.000002715164,0.00001011835,0.0001563236,0.0002569862,0.000004327233,0.00009159413,0.0001430971,0.006320546,0.0002132724,0.6883808,0.3044102,0.00001014434],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002051202,0.02181383,0.6867278,0.02296164,0.002422654,0.00009903875,0.0005980079,0.0008299446,0.2624958],"genre_scores_gemma":[0.1001687,0.07977784,0.6115652,0.007340027,0.00362776,0.0005981333,0.001316608,0.0009305354,0.1946752],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01537417,"threshold_uncertainty_score":0.05143178,"prediction_status":"machine_predicted_unvalidated"},"labels":[],"label_agreement":null}]}