{"id":"W4309098499","doi":"10.2196/40765","title":"Recruitment and Retention in Remote Research: Learnings From a Large, Decentralized Real-world Study","year":2022,"lang":"en","type":"article","venue":"JMIR Formative Research","topic":"Mobile Crowdsensing and Crowdsourcing","field":"Computer Science","cited_by":30,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Vector Institute; Centre for Addiction and Mental Health","funders":"National Institute on Aging","keywords":"Incentive; Logistic regression; Data collection; Cohort; Cohort study; Medicine; Environmental health; Applied psychology; Psychology; Gerontology; Statistics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.3155628,0.0008715483,0.002010924,0.001822884,0.005578767,0.008171388,0.005610925,0.003625782,0.002980089],"category_scores_gemma":[0.3893729,0.001127344,0.001690484,0.002065114,0.00851757,0.01136154,0.01027759,0.004983295,0.001034937],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004789625,"about_ca_system_score_gemma":0.01710929,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005960955,"about_ca_topic_score_gemma":0.01269008,"domain_scores_codex":[0.753104,0.2124182,0.007337847,0.00989943,0.01254086,0.004699678],"domain_scores_gemma":[0.5412295,0.3090788,0.0342865,0.07312931,0.02892053,0.01335544],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001498948,0.003696572,0.4761759,0.003577985,0.001097254,0.001286465,0.1051832,0.003321735,0.001760091,0.01086917,0.01973613,0.3717965],"study_design_scores_gemma":[0.002566089,0.01533488,0.5149516,0.01634078,0.001768959,0.001893698,0.159806,0.04969465,0.003793692,0.1391187,0.09366897,0.001061884],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.730404,0.00611153,0.149747,0.08983991,0.001599206,0.01086461,0.0009655984,0.0004696074,0.009998534],"genre_scores_gemma":[0.8920792,0.002158019,0.08438162,0.009902169,0.001406222,0.008672841,0.0004912737,0.0001813638,0.0007272933],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6844372,"threshold_uncertainty_score":0.8440329,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2063275721651562,"score_gpt":0.4515574738549148,"score_spread":0.2452299016897586,"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."}}