{"id":"W3215656606","doi":"10.21203/rs.3.rs-1011736/v1","title":"Remote Mentoring Optimizes Virtual Collection of Patient-Reported Data: A Prospective Cohort Study with Adaptive Design Conducted in COVID-19 Era.","year":2021,"lang":"en","type":"preprint","venue":"Research Square","topic":"Cancer survivorship and care","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"McMaster University; University of Toronto","funders":"","keywords":"Coronavirus disease 2019 (COVID-19); Data collection; Prospective cohort study; Cohort; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); 2019-20 coronavirus outbreak; Medicine; Computer science; Statistics; Virology; Internal medicine; Mathematics; Disease","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":[],"consensus_categories":[],"category_scores_codex":[0.007380577,0.0004029327,0.0003002801,0.0003394891,0.0007008063,0.0009674664,0.000876912,0.0004658658,0.003566754],"category_scores_gemma":[0.0171713,0.0002169992,0.0004940818,0.0003660163,0.0004505704,0.0005883297,0.001324969,0.0007336746,0.000559178],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004677581,"about_ca_system_score_gemma":0.001537209,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002989239,"about_ca_topic_score_gemma":0.004025589,"domain_scores_codex":[0.9954354,0.00348253,0.0001258232,0.0004273581,0.0002185569,0.0003103462],"domain_scores_gemma":[0.9917747,0.003593991,0.0009441281,0.001859443,0.0004771214,0.001350567],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.04096552,0.03343998,0.7135372,0.0003041153,0.0005785733,0.0003341062,0.003568328,0.002001585,0.003936831,0.0004662453,0.004595765,0.1962718],"study_design_scores_gemma":[0.005420593,0.06106302,0.9178482,0.0001218614,0.0003777801,0.0003104942,0.002718077,0.005433944,0.002035928,0.0006227383,0.003937118,0.0001101573],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9973482,0.00008255919,0.001135288,0.0001305756,0.00003686818,0.0003978616,0.000267062,0.00003343043,0.0005681994],"genre_scores_gemma":[0.9939821,0.00006775834,0.003784723,0.00008676315,0.00003880776,0.000974581,0.0002466147,0.00001986796,0.0007986461],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007380577,"threshold_uncertainty_score":0.0390327,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1411659597427247,"score_gpt":0.4156465961914373,"score_spread":0.2744806364487127,"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."}}