{"id":"W4398332641","doi":"10.7910/dvn/pkjufn/xlo5vz","title":"FCC2003.320.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); Meteorology; Ran; Atmospheric sciences; Environmental science; Geography; Geology; Physics; Computer science; Magnetic field; Engineering; Aerospace 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":[0.001422758,0.002576017,0.001677648,0.003697659,0.0007381805,0.002873345,0.003873959,0.002743743,0.1256808],"category_scores_gemma":[0.007997953,0.0009086495,0.00160545,0.006625933,0.0005258094,0.001450943,0.001882284,0.001713844,0.1516059],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001811622,"about_ca_system_score_gemma":0.002168296,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03546748,"about_ca_topic_score_gemma":0.04609732,"domain_scores_codex":[0.998989,0.0002471276,0.0001141996,0.0002894372,0.0001858639,0.0001742248],"domain_scores_gemma":[0.9976811,0.0006469978,0.0002365418,0.0006172218,0.0004985383,0.000319465],"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":[0.00004707692,0.00001023962,0.0003221987,0.0002916508,0.00002308771,0.000007645401,0.000006744097,0.000226025,0.00002763466,0.0002703662,0.9978054,0.0009618154],"study_design_scores_gemma":[0.0006012607,0.00003138774,0.002853255,0.0003885771,0.00004730701,0.00005985176,0.00004701861,0.001219522,0.000270164,0.00206118,0.9923853,0.00003535773],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005991674,0.00006000783,0.00003640492,0.00007857392,0.00002340498,0.000005376552,0.9987807,0.0003651154,0.0005905157],"genre_scores_gemma":[0.0003685783,0.00005847842,0.000143883,0.00008935614,0.00001333507,0.00003655886,0.9986431,0.00009144559,0.0005552539],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8743192,"threshold_uncertainty_score":0.4204443,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01992432435318893,"score_gpt":0.2752857025316037,"score_spread":0.2553613781784148,"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."}}