{"id":"W4398338294","doi":"10.7910/dvn/pkjufn/jyfyob","title":"FCC2001.343.ran","year":2020,"lang":"en","type":"dataset","venue":"Harvard Dataverse","topic":"Cardiovascular Health and Disease Prevention","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Natural Resources Canada","funders":"","keywords":"Range (aeronautics); Earth's magnetic field; Meteorology; Environmental science; Atmospheric sciences; Geography; Geology; Physics; Materials science; Magnetic field","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":[0.001329495,0.002491778,0.001735172,0.003796879,0.0007545631,0.003033744,0.003727257,0.002723394,0.1471564],"category_scores_gemma":[0.008452422,0.0009431855,0.00155408,0.006988048,0.0004908658,0.001424307,0.001914204,0.001601946,0.1639011],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001792787,"about_ca_system_score_gemma":0.00216107,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03453902,"about_ca_topic_score_gemma":0.04467754,"domain_scores_codex":[0.9990512,0.0002298009,0.0001032516,0.0002843812,0.0001668718,0.0001645083],"domain_scores_gemma":[0.9975756,0.000759722,0.0002483026,0.0006074954,0.0004875271,0.0003213794],"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":[0.00004636112,0.000008932791,0.0003600844,0.0003389085,0.00002488227,0.000007794679,0.000007454045,0.0002118835,0.00002608333,0.0002867081,0.9976591,0.001021804],"study_design_scores_gemma":[0.000593149,0.00002809228,0.002761564,0.0004465808,0.00005157082,0.00005525433,0.00004614071,0.001008291,0.0002379635,0.00217195,0.9925647,0.00003480669],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005155002,0.00006607454,0.0000348892,0.00007838647,0.00002063837,0.000004844036,0.9988003,0.0003498438,0.0005934624],"genre_scores_gemma":[0.0004036201,0.00007498961,0.0001501188,0.0001078448,0.00001530334,0.00004146742,0.998471,0.0001107904,0.0006248893],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8528436,"threshold_uncertainty_score":0.492287,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01976153797269264,"score_gpt":0.2759116896298448,"score_spread":0.2561501516571522,"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."}}