{"id":"W4398751791","doi":"10.7910/dvn/pkjufn/pjnedq","title":"FCC2002.346.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; Environmental science; Atmospheric sciences; Meteorology; Geology; Geography; Physics; Computer science; 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":[0.001341727,0.002494353,0.001698098,0.00381282,0.000752599,0.003032711,0.003694162,0.002715095,0.1470448],"category_scores_gemma":[0.008312394,0.0009280527,0.001558745,0.006954543,0.0004936302,0.001436406,0.001897967,0.001601968,0.1672092],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001742705,"about_ca_system_score_gemma":0.002152485,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03392724,"about_ca_topic_score_gemma":0.0436196,"domain_scores_codex":[0.9990525,0.0002294641,0.0001023728,0.0002825495,0.0001689636,0.0001640975],"domain_scores_gemma":[0.9976356,0.0007191032,0.0002391423,0.0006038515,0.0004789043,0.0003233877],"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":[0.00004554212,0.000009152379,0.0003450781,0.0003169104,0.0000240138,0.000007690607,0.000007231378,0.0002040278,0.00002624286,0.0002758091,0.9977376,0.001000656],"study_design_scores_gemma":[0.0005832732,0.00002852201,0.002711456,0.0004195485,0.00004942639,0.00005423491,0.00004635517,0.0009866052,0.0002359137,0.002076179,0.9927742,0.00003416878],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005249891,0.0000637919,0.00003445275,0.00007892986,0.00002143621,0.000004952599,0.9987907,0.0003516073,0.0006018098],"genre_scores_gemma":[0.0003898233,0.00007115135,0.0001473495,0.0001048828,0.00001532063,0.00004075177,0.9984895,0.0001089078,0.0006322704],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8529552,"threshold_uncertainty_score":0.4919139,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0198179097441933,"score_gpt":0.2741131898192298,"score_spread":0.2542952800750365,"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."}}