{"id":"W4398283243","doi":"10.7910/dvn/pkjufn/d9yj5k","title":"FCC2003.213.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; Ran; Environmental science; Meteorology; Atmospheric sciences; Remote sensing; Geology; Physics; Computer science; 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":[0.001285722,0.002580896,0.001653972,0.003571054,0.0007715505,0.003105029,0.003780036,0.002683877,0.1479758],"category_scores_gemma":[0.007389218,0.0009480932,0.001583332,0.006537933,0.000504248,0.001466076,0.00193901,0.001676826,0.1777652],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001769781,"about_ca_system_score_gemma":0.002141911,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03453471,"about_ca_topic_score_gemma":0.04557863,"domain_scores_codex":[0.9990646,0.0002175128,0.0001066969,0.0002745883,0.0001699555,0.000166667],"domain_scores_gemma":[0.9978033,0.0006161693,0.0002118486,0.0005898264,0.00047703,0.0003018529],"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":[0.00004380746,0.000009661061,0.0002947033,0.0002823583,0.00002128985,0.000007584819,0.000007062591,0.0001989206,0.00002822185,0.000280614,0.9979081,0.0009177969],"study_design_scores_gemma":[0.000541624,0.0000268177,0.002412051,0.0003479176,0.00004017775,0.0000496377,0.00004446389,0.0009525246,0.0002478174,0.001911038,0.9933949,0.00003109378],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005149166,0.00005208094,0.0000345116,0.00006934328,0.00002226554,0.000005057319,0.9987025,0.0003863431,0.0006764473],"genre_scores_gemma":[0.0003315861,0.00005334361,0.0001358108,0.0000855786,0.00001194216,0.00003370338,0.9986356,0.0001081921,0.0006041537],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8520241,"threshold_uncertainty_score":0.4950285,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01974096343116817,"score_gpt":0.2748738297652519,"score_spread":0.2551328663340837,"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."}}