{"id":"W4398316991","doi":"10.7910/dvn/pkjufn/tgx9oq","title":"FCC2001.014.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":"Earth's magnetic field; Range (aeronautics); Ran; Absorption (acoustics); Environmental science; Meteorology; Atmospheric sciences; Remote sensing; Geology; Physics; Materials science; Computer science; Magnetic field; Optics","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":[0.001367618,0.002341631,0.001716484,0.003561094,0.0007484697,0.002845087,0.003739564,0.002655487,0.1450103],"category_scores_gemma":[0.009080393,0.0008928006,0.001502006,0.006459553,0.0004843373,0.001385576,0.001886492,0.00161633,0.1503319],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001806223,"about_ca_system_score_gemma":0.002262006,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03583596,"about_ca_topic_score_gemma":0.04692203,"domain_scores_codex":[0.9990304,0.0002429692,0.00010316,0.0002917636,0.0001694588,0.0001623379],"domain_scores_gemma":[0.9974203,0.0008114643,0.0002680863,0.000643376,0.0005203444,0.0003363745],"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":[0.00004957831,0.00000883028,0.0003978421,0.0003289439,0.00002566309,0.000007661673,0.000007037535,0.0002067763,0.00002356442,0.0002841641,0.997645,0.001014976],"study_design_scores_gemma":[0.0006410013,0.00002778486,0.003099461,0.0004605587,0.00005553002,0.00005609662,0.00004616297,0.0009974226,0.0002343298,0.002237058,0.9921092,0.00003537109],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005405183,0.00006585876,0.00003430466,0.00008577592,0.0000212625,0.00000490803,0.9988794,0.0003099843,0.0005445296],"genre_scores_gemma":[0.0004428361,0.0000770406,0.0001604441,0.0001181363,0.00001770437,0.00004642469,0.9983584,0.00010782,0.0006711746],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8549897,"threshold_uncertainty_score":0.4851078,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01948323238178095,"score_gpt":0.2752680452287747,"score_spread":0.2557848128469938,"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."}}