{"id":"W4398323298","doi":"10.7910/dvn/pkjufn/fww2dv","title":"FCC2002.254.ran","year":2020,"lang":"sr","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; Atmospheric sciences; Environmental science; Physics; Aerospace engineering; Magnetic field; Engineering","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":[0.001475389,0.002469768,0.001692381,0.003682044,0.0007620277,0.003057886,0.0039916,0.002654804,0.1554321],"category_scores_gemma":[0.008148683,0.0009554456,0.001543086,0.00639031,0.000505913,0.001488351,0.002,0.001640459,0.1956922],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001571892,"about_ca_system_score_gemma":0.002043456,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02938431,"about_ca_topic_score_gemma":0.03599494,"domain_scores_codex":[0.9989429,0.0002549815,0.0001161691,0.0003080889,0.0001974337,0.0001803132],"domain_scores_gemma":[0.9974861,0.0006438245,0.0002392256,0.0007357038,0.0005375214,0.000357655],"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":[0.00004354331,0.000009236672,0.0002650332,0.0002294511,0.00001928243,0.000006558832,0.000006325175,0.0001567557,0.00002943748,0.0002415706,0.9980642,0.0009286404],"study_design_scores_gemma":[0.0005778553,0.00003332448,0.002585669,0.0002993292,0.00003926441,0.00005107062,0.00004249903,0.001001672,0.0002638245,0.001729579,0.9933439,0.00003191589],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005582308,0.00004664754,0.00003802047,0.0000757568,0.00002321529,0.000005776658,0.9985662,0.0004932391,0.0006954689],"genre_scores_gemma":[0.0003457027,0.00004391903,0.0001405548,0.00008208418,0.0000139689,0.0000354087,0.9986174,0.0001250289,0.0005959013],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8445679,"threshold_uncertainty_score":0.5199721,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01981747953019767,"score_gpt":0.2716693570327376,"score_spread":0.25185187750254,"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."}}