{"id":"W7073862857","doi":"","title":"Harnessing genomics to improve health in India – an executive course to support genomics policy","year":2004,"lang":"en","type":"article","venue":"TSpace","topic":"Glass properties and applications","field":"Materials Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Hospital for Sick Children; Fogarty International Center; International Development Research Centre; Canadian Institutes of Health Research; Genome Canada; Ontario Genomics; Ontario Genomics Institute; University of Toronto; World Health Organization; GlaxoSmithKline","keywords":"Genomics; Health care; MEDLINE; Course (navigation); Identification (biology)","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003210354,0.0001383448,0.0002031584,0.0001050459,0.0001622984,0.0001190559,0.0002996639,0.00004971879,0.0000361784],"category_scores_gemma":[0.00002448099,0.000135991,0.00002210825,0.0002861711,0.00004012691,0.0001240054,0.0001436399,0.00008937971,0.0004052828],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007916985,"about_ca_system_score_gemma":0.001202915,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00560029,"about_ca_topic_score_gemma":0.0007409561,"domain_scores_codex":[0.998751,0.00002807106,0.0002325942,0.0003827375,0.0001035293,0.0005020686],"domain_scores_gemma":[0.9991035,0.000008287959,0.00008523404,0.0003945619,0.0000440766,0.0003643434],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00004112784,0.0001638423,0.00008353312,0.00001381942,0.000002283687,0.00000385816,0.03177074,0.002586942,0.9524228,0.007048594,0.0006638372,0.005198621],"study_design_scores_gemma":[0.002498003,0.00224962,0.04044973,0.0001277445,0.00002097208,0.00004454788,0.03059571,0.0002050906,0.7771059,0.004196426,0.1409737,0.001532527],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.97811,0.00002243395,0.001597657,0.01852422,0.0001221649,0.0006562514,0.00004649677,0.00005634757,0.0008643947],"genre_scores_gemma":[0.9764566,0.00001323073,0.01718661,0.005479898,0.0001885363,0.00008514847,0.00001131304,0.00003151405,0.0005471266],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1753168,"threshold_uncertainty_score":0.8466001,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02488376058524994,"score_gpt":0.3450723553597722,"score_spread":0.3201885947745222,"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."}}