{"id":"W2078712287","doi":"10.1503/cmaj.109-4757","title":"India moves to boost its Parsi population","year":2014,"lang":"en","type":"article","venue":"Canadian Medical Association Journal","topic":"Global Maternal and Child Health","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Fertility; Population; Medicine; Demography; Socioeconomics; Ancient history; History; Sociology; Environmental health","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001033697,0.000635444,0.0004428901,0.001340718,0.001976581,0.002773838,0.001373162,0.001618596,0.02986631],"category_scores_gemma":[0.002127852,0.0002246718,0.0007496036,0.001252974,0.00134491,0.001435504,0.00368912,0.002761291,0.009408433],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002538676,"about_ca_system_score_gemma":0.008841704,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0235326,"about_ca_topic_score_gemma":0.02235825,"domain_scores_codex":[0.9991813,0.00009588215,0.00002813545,0.0000742874,0.0002289577,0.0003914154],"domain_scores_gemma":[0.9979672,0.0001896301,0.0001121642,0.0001340733,0.0006297152,0.0009672217],"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":[0.0002606095,0.0003153177,0.02534949,0.0012271,0.00009480939,0.001656565,0.004282657,0.0004865426,0.005378625,0.06805531,0.5924336,0.3004593],"study_design_scores_gemma":[0.00003683641,0.0001584723,0.0318855,0.000220291,0.00004921679,0.001095477,0.002606523,0.0002192982,0.00120459,0.004342114,0.9581419,0.00003976979],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.1604618,0.01770899,0.005629235,0.3548882,0.01505651,0.0002743514,0.00598849,0.005178605,0.4348139],"genre_scores_gemma":[0.6611716,0.01620822,0.009104757,0.1608925,0.005702101,0.0002449086,0.004427358,0.0005633845,0.1416853],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.02986631,"threshold_uncertainty_score":0.09991276,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005610168792352975,"score_gpt":0.2482897131201271,"score_spread":0.2426795443277741,"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."}}