{"id":"W4398321770","doi":"10.7910/dvn/o7eggp/fntj6k","title":"childmarr_20Dec2018.tab","year":2018,"lang":"en","type":"dataset","venue":"Harvard Dataverse","topic":"Demographic Trends and Gender Preferences","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Computer science; Geography; Statistics; Mathematics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0007993703,0.001743026,0.001210705,0.003952068,0.0006712039,0.002674844,0.002218759,0.001531734,0.1438952],"category_scores_gemma":[0.005645853,0.0007741115,0.001019815,0.007638945,0.0003292895,0.00161239,0.001688052,0.001585853,0.1408836],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001482065,"about_ca_system_score_gemma":0.002128899,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03745183,"about_ca_topic_score_gemma":0.05300057,"domain_scores_codex":[0.9993574,0.00006506229,0.00009163588,0.0001808372,0.0001493777,0.0001557246],"domain_scores_gemma":[0.9982262,0.0003873922,0.0002902983,0.0003164029,0.0005097917,0.0002697931],"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":[0.00004101025,0.00001048576,0.001065687,0.0002350164,0.00001187616,0.00001179303,0.00001647832,0.00008957717,0.00002599486,0.0002601211,0.9968824,0.001349413],"study_design_scores_gemma":[0.0002995892,0.00001777161,0.008651801,0.0002963093,0.00002600627,0.00006647922,0.0000962675,0.0002551478,0.0001904777,0.0007235982,0.9893511,0.00002545323],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0000975865,0.0000375437,0.00001685413,0.00004613618,0.00001825587,0.000003252573,0.9991578,0.0001280877,0.0004945255],"genre_scores_gemma":[0.0005168757,0.0000672138,0.00008065757,0.00004929995,0.00001586104,0.00004149651,0.9980382,0.00006412388,0.001126315],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8561049,"threshold_uncertainty_score":0.4813773,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03037626605030779,"score_gpt":0.2970540578979711,"score_spread":0.2666777918476633,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}