{"id":"W4402661657","doi":"10.1249/01.mss.0001062112.87359.8b","title":"Cancer Exercise Mobile App: Reporting The First Analytics","year":2024,"lang":"en","type":"article","venue":"Medicine & Science in Sports & Exercise","topic":"Mobile Health and mHealth Applications","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Analytics; Mobile apps; Cancer; Computer science; Medicine; Data science; World Wide Web; Internal medicine","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007904936,0.001593847,0.001151704,0.007845898,0.00125508,0.003435246,0.0009515574,0.001326413,0.02073184],"category_scores_gemma":[0.05543896,0.000636331,0.001327299,0.004379889,0.0004698751,0.003062759,0.003187925,0.002128213,0.02515251],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001257357,"about_ca_system_score_gemma":0.004359382,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005769353,"about_ca_topic_score_gemma":0.007454332,"domain_scores_codex":[0.9896863,0.001681214,0.003257053,0.001041726,0.003603253,0.0007304405],"domain_scores_gemma":[0.9165998,0.02551151,0.009691624,0.006710541,0.03905867,0.002427845],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.001111705,0.0005297478,0.06994253,0.006378286,0.0001642197,0.0004534774,0.0009926545,0.0003270505,0.001671602,0.001016131,0.764293,0.1531197],"study_design_scores_gemma":[0.0002675952,0.0007751659,0.1801136,0.004017166,0.0002802195,0.0009795623,0.001204859,0.001971029,0.008407849,0.001255541,0.8003771,0.0003503686],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.04120231,0.003037769,0.009749962,0.004106666,0.001446789,0.0101401,0.8706331,0.02031477,0.03936853],"genre_scores_gemma":[0.1114344,0.003791511,0.03798486,0.003848419,0.001450235,0.0395503,0.7691365,0.004901087,0.02790268],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02073184,"threshold_uncertainty_score":0.06935489,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04983242530409025,"score_gpt":0.4382248668052777,"score_spread":0.3883924415011875,"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."}}