{"id":"W7071702758","doi":"","title":"1064: Tracking Food Intake vs. Intuitive Eating When Cutting &amp; Bulking, the Pros &amp; Cons of Lifting Wraps &amp; Sleeves, How to Overcome Mental Blocks to Lifting Heavy &amp; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.003159082,0.0007173924,0.0002625763,0.000328382,0.008865295,0.004895795,0.001060319,0.003349999,0.04282606],"category_scores_gemma":[0.00647965,0.0006423457,0.0003135059,0.0003765616,0.004077377,0.004169074,0.002671644,0.004246623,0.01710896],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003871248,"about_ca_system_score_gemma":0.002035846,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05142067,"about_ca_topic_score_gemma":0.1426824,"domain_scores_codex":[0.9982768,0.0009946109,0.00004205561,0.0002001549,0.0002876308,0.0001987328],"domain_scores_gemma":[0.9982812,0.0005311733,0.0001028972,0.00008588831,0.0005089031,0.0004898594],"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":[0.0002756177,0.0001202447,0.006514535,0.0001330165,0.00001067324,0.0003065852,0.01926049,0.00008470007,0.001233699,0.007181218,0.8911014,0.07377785],"study_design_scores_gemma":[0.00006101968,0.0002453701,0.01331886,0.0002905331,0.00002392589,0.0005740412,0.04854632,0.0006675707,0.00196481,0.005712418,0.9284803,0.0001147507],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.07572826,0.004672875,0.009417975,0.2475404,0.007840237,0.000260845,0.001164806,0.001836415,0.6515382],"genre_scores_gemma":[0.3366213,0.003695953,0.02014735,0.08418164,0.001192688,0.0005871675,0.001144458,0.001369945,0.5510595],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.9571739,"threshold_uncertainty_score":0.1432675,"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."}}