{"id":"W4398542941","doi":"10.7910/dvn/pkjufn/swxcy7","title":"FCC2003.074.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; Remote sensing; Geology; Physics; Aerospace engineering; Engineering; 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":[0.001417382,0.002386628,0.001693704,0.003571682,0.0007401134,0.002896209,0.003748133,0.002652344,0.1396185],"category_scores_gemma":[0.009001247,0.0008817422,0.001573375,0.006509189,0.0004964936,0.001403279,0.001895033,0.001644843,0.1555344],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001753063,"about_ca_system_score_gemma":0.002268937,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03547978,"about_ca_topic_score_gemma":0.04634465,"domain_scores_codex":[0.9990035,0.0002454385,0.0001076613,0.0002949011,0.0001770739,0.000171439],"domain_scores_gemma":[0.9974563,0.0007582513,0.00025907,0.0006587447,0.0005302253,0.000337515],"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":[0.00004717431,0.000009085428,0.0003855766,0.0002980826,0.00002516575,0.000007565041,0.000006820615,0.0002024418,0.00002486455,0.0002656071,0.9977409,0.0009868471],"study_design_scores_gemma":[0.0006197714,0.0000284206,0.003085122,0.000430874,0.00005431789,0.00005706996,0.00004800857,0.001035749,0.0002485701,0.002181213,0.9921754,0.0000354251],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005561648,0.00006263341,0.00003499862,0.00008344517,0.00002272225,0.00000509856,0.9988635,0.000328558,0.0005434367],"genre_scores_gemma":[0.0004122704,0.00006971948,0.0001550553,0.0001104564,0.00001692948,0.00004383365,0.9984428,0.000104534,0.0006443636],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8603815,"threshold_uncertainty_score":0.4670703,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01973706749555086,"score_gpt":0.2748691842451595,"score_spread":0.2551321167496087,"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."}}