{"id":"W7071702758","doi":"","title":"1064: Tracking Food Intake vs. Intuitive Eating When Cutting & Bulking, the Pros & Cons of Lifting Wraps & Sleeves, How to Overcome Mental Blocks to Lifting Heavy & MORE","year":2019,"lang":"en","type":"other","venue":"Bulletin of Miscellaneous Information (Royal Gardens Kew)","topic":"QR Code Applications and Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Tracking (education); Adventure; Flexibility (engineering); Aside; Lift (data mining)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0008580776,0.0006999148,0.0008577518,0.0003817397,0.0003909619,0.0004673058,0.002181686,0.0005137766,0.00368635],"category_scores_gemma":[0.001036788,0.0006274233,0.0002755309,0.0001318264,0.0002226137,0.000005470216,0.001445416,0.0007777288,0.001871032],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001687693,"about_ca_system_score_gemma":0.00009919693,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002646049,"about_ca_topic_score_gemma":0.003675858,"domain_scores_codex":[0.9961787,0.0001196829,0.00126444,0.000737156,0.0009254892,0.000774507],"domain_scores_gemma":[0.9955819,0.0005097437,0.001621925,0.001714705,0.0003873265,0.000184379],"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":[0.00002932045,0.00006064633,0.0000987013,0.0003290732,0.0001410155,0.000001106893,0.00818087,0.0005117888,0.00003766777,0.0004287791,0.9768903,0.01329075],"study_design_scores_gemma":[0.0003541037,0.0001618979,0.00002546136,0.001259926,0.00004155896,0.00008148357,0.000772817,0.0001094102,0.0001258066,0.00005472461,0.9963558,0.0006569654],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.004558782,0.0003199142,0.003050909,0.004385848,0.0003965905,0.003031621,0.0002599346,0.0008748899,0.9831215],"genre_scores_gemma":[0.02111733,0.00005492285,0.1644924,0.001108302,0.0002031138,0.0002122217,0.0001690912,0.0001909641,0.8124517],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.1706698,"threshold_uncertainty_score":0.9996177,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01375009119949907,"score_gpt":0.21594963541896,"score_spread":0.2021995442194609,"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."}}