{"id":"W4398315567","doi":"10.7910/dvn/pkjufn/y7xhkb","title":"FCC2002.088.ran","year":2020,"lang":"el","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); Environmental science; Meteorology; Remote sensing; Atmospheric sciences; Physics; Geology; Magnetic field; Aerospace engineering; 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":[0.001481615,0.002406453,0.00170817,0.003701161,0.0007716652,0.0030137,0.003880672,0.002748477,0.1492206],"category_scores_gemma":[0.00918672,0.0008969316,0.001503726,0.006253886,0.0005054479,0.001438055,0.001983114,0.001610551,0.1719024],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001688744,"about_ca_system_score_gemma":0.002166638,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03039914,"about_ca_topic_score_gemma":0.03792449,"domain_scores_codex":[0.9989738,0.0002524131,0.0001056691,0.0003079257,0.000181382,0.0001788723],"domain_scores_gemma":[0.9973311,0.0007807913,0.0002677077,0.0007102714,0.0005470113,0.0003630149],"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":[0.00004892566,0.000009370018,0.0003715353,0.000270503,0.00002318843,0.000007395242,0.000006377493,0.0001711752,0.00002477362,0.0002376629,0.9978059,0.001023079],"study_design_scores_gemma":[0.0006921579,0.0000336567,0.003268594,0.0004174681,0.00005542494,0.00005769165,0.00004798998,0.001060035,0.0002663296,0.002100471,0.9919634,0.00003679881],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005927959,0.00006105782,0.00003682361,0.00009396936,0.00002256803,0.000005505495,0.9987195,0.0004090672,0.0005923875],"genre_scores_gemma":[0.0004402827,0.00006373652,0.0001471622,0.0001193102,0.00001900526,0.00004614107,0.9983911,0.0001140398,0.0006592438],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8507794,"threshold_uncertainty_score":0.4991928,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02069068419926492,"score_gpt":0.2721937963162187,"score_spread":0.2515031121169538,"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."}}