{"id":"W4398318808","doi":"10.7910/dvn/pkjufn/pta0ed","title":"FCC2001.291.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; 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":[0.00129409,0.002507911,0.001692627,0.003687671,0.0007676537,0.003019422,0.003628492,0.002774304,0.1476911],"category_scores_gemma":[0.008333508,0.0009439928,0.001579534,0.006803703,0.0004797287,0.001409566,0.001885388,0.001614074,0.1613354],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001817778,"about_ca_system_score_gemma":0.002238966,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03677518,"about_ca_topic_score_gemma":0.04842637,"domain_scores_codex":[0.9990509,0.0002283441,0.0001044198,0.0002818773,0.0001668547,0.0001675357],"domain_scores_gemma":[0.9975727,0.0007804603,0.0002419578,0.0005860211,0.000501873,0.0003169251],"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":[0.00004589916,0.000009106623,0.0003524817,0.0003486208,0.00002459961,0.000007887623,0.000007689666,0.0002082714,0.00002641469,0.0002832431,0.9977155,0.0009702751],"study_design_scores_gemma":[0.0005962895,0.00002841078,0.002806614,0.0004603738,0.00005182819,0.00005343369,0.00004728512,0.0009764186,0.0002366647,0.002096312,0.9926121,0.00003432895],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0000502785,0.00006255692,0.00003241612,0.00007591234,0.00002032391,0.000004812026,0.9988222,0.0003356366,0.0005958946],"genre_scores_gemma":[0.0003883905,0.00006989981,0.0001457158,0.0001062985,0.00001406196,0.00004002915,0.9985073,0.0001095276,0.0006187282],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8523089,"threshold_uncertainty_score":0.4940761,"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."}}