{"id":"W2608687977","doi":"10.1093/sleepj/zsx050.791","title":"0792 SLEEP OPTIMIZATION IMPROVES MOOD DIFFERENTLY BETWEEN CANADIAN NATIONAL TEAM CURLERS AND ROWERS","year":2017,"lang":"en","type":"article","venue":"SLEEP","topic":"High Altitude and Hypoxia","field":"Biochemistry, Genetics and Molecular Biology","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Sleep & Circadian Network; University of Calgary","funders":"","keywords":"Mood; Sleep (system call); Psychology; Medicine; Psychiatry; Clinical psychology; Computer science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006939745,0.0001133872,0.00009416804,0.00003986379,0.0003368334,0.00009491992,0.0001890267,0.0001281776,0.00003041507],"category_scores_gemma":[0.00007529183,0.0001135888,0.00003673464,0.00001697538,0.00008009718,0.00001218005,0.00008137275,0.00006344507,0.000009369192],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002938546,"about_ca_system_score_gemma":0.00005870571,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002955662,"about_ca_topic_score_gemma":0.01999503,"domain_scores_codex":[0.9993132,0.00001464469,0.0001025703,0.0002461997,0.0001116189,0.000211748],"domain_scores_gemma":[0.9994418,0.000003089309,0.00006708354,0.000240608,0.0000579132,0.0001894882],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001579387,0.000224606,0.7030694,0.0001066312,0.0009439767,0.00002320817,0.0006186622,0.005101942,0.2153456,0.001287523,0.03152206,0.04159846],"study_design_scores_gemma":[0.00532731,0.0008260999,0.7600204,0.00004340016,0.0002896804,0.00003139313,0.0001761834,0.01324581,0.04734024,0.0007724246,0.1700263,0.00190079],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.96869,0.0002032635,0.001596857,0.0010609,0.0002352078,0.0002235377,0.00008614946,0.00001345122,0.02789063],"genre_scores_gemma":[0.9980592,0.00004926799,0.0006352249,0.0001700016,0.0002860016,0.00001025884,0.0002787652,0.00001550286,0.000495789],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1680053,"threshold_uncertainty_score":0.9978875,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01009295193235787,"score_gpt":0.2437595531836964,"score_spread":0.2336666012513386,"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."}}