{"id":"W4398335102","doi":"10.7910/dvn/pkjufn/camj6c","title":"FCC2002.308.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; Atmospheric sciences; Environmental science; Geomagnetic latitude; Remote sensing; Physics; Geology; 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":[0.001352877,0.002368941,0.001656807,0.003530376,0.0007139641,0.002933219,0.00367401,0.002613978,0.1447931],"category_scores_gemma":[0.007949771,0.0008743648,0.001410927,0.006622911,0.0004903257,0.001442354,0.001834194,0.001574017,0.1668793],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001746309,"about_ca_system_score_gemma":0.002063708,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0325835,"about_ca_topic_score_gemma":0.04086088,"domain_scores_codex":[0.9990401,0.00023655,0.0001071425,0.0002796047,0.0001732987,0.0001632957],"domain_scores_gemma":[0.9977003,0.000642557,0.0002385437,0.0006045159,0.0004849269,0.0003292274],"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":[0.00004853287,0.00000887642,0.0003178661,0.0002816417,0.00002099868,0.000007269202,0.000006371126,0.0001971463,0.0000251137,0.0002762875,0.9978626,0.0009471595],"study_design_scores_gemma":[0.0005332906,0.00002761587,0.002656293,0.0003668524,0.00004089719,0.00005072884,0.00004143195,0.0009558451,0.0002310364,0.001942538,0.9931222,0.00003136701],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005343469,0.00005601403,0.00003471456,0.00007629846,0.00002153109,0.000005026707,0.9987602,0.0003317945,0.0006609845],"genre_scores_gemma":[0.0003914992,0.00005792769,0.0001349432,0.00009386948,0.0000138117,0.00003727825,0.9985507,0.00009719768,0.0006227228],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8552069,"threshold_uncertainty_score":0.4843811,"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."}}