{"id":"W4398570989","doi":"10.7910/dvn/28075/azq6y6","title":"events.2015.20160413141412.tab","year":2016,"lang":"en","type":"dataset","venue":"Harvard Dataverse","topic":"Travel-related health issues","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lockheed Martin (Canada)","funders":"","keywords":"Computer science","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":[0.0008560874,0.002072417,0.001280209,0.004214327,0.000669192,0.003178601,0.002252533,0.001805107,0.1626868],"category_scores_gemma":[0.005007375,0.0009186281,0.001143914,0.007618015,0.0004425674,0.0017835,0.002124249,0.001639562,0.1852265],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001919698,"about_ca_system_score_gemma":0.002084368,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0320459,"about_ca_topic_score_gemma":0.05141448,"domain_scores_codex":[0.9992563,0.0000908276,0.0001259497,0.0002003003,0.0001682504,0.0001584495],"domain_scores_gemma":[0.9983612,0.0003637851,0.0002917796,0.0003072791,0.0003643695,0.0003115444],"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":[0.00005229041,0.00001203548,0.0006846726,0.0003693484,0.00001640848,0.00001398648,0.00001737892,0.0001748023,0.00005213426,0.0005020868,0.9968488,0.001256087],"study_design_scores_gemma":[0.0002550721,0.00001814432,0.004030506,0.0002796588,0.00002149757,0.00004754727,0.00005954176,0.0002986501,0.0002200218,0.001121426,0.9936228,0.00002514419],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005633803,0.00003678555,0.00001979181,0.00004768774,0.00001873429,0.000003651058,0.9990391,0.000150058,0.0006279315],"genre_scores_gemma":[0.0002907101,0.00005822836,0.00005711137,0.00004165173,0.000009803814,0.00001895914,0.9986645,0.00005478312,0.0008042892],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8373132,"threshold_uncertainty_score":0.5442414,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02375264205609198,"score_gpt":0.3165580355860415,"score_spread":0.2928053935299496,"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."}}