{"id":"W4205747615","doi":"10.2196/34176","title":"The Accessibility of YouTube Fitness Videos for Individuals Who Are Disabled Before and During the COVID-19 Pandemic: Preliminary Application of a Text Analytics Approach","year":2022,"lang":"en","type":"article","venue":"JMIR Formative Research","topic":"Inclusion and Disability in Education and Sport","field":"Social Sciences","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Analytics; Coronavirus disease 2019 (COVID-19); Python (programming language); Pandemic; Psychology; Internet privacy; Physical fitness; Content analysis; Computer science; Multimedia; Applied psychology; Medicine; Physical therapy; Database; Disease; Sociology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007599426,0.0005019543,0.0004943536,0.007689336,0.001358488,0.003525137,0.0008322111,0.0007901039,0.007483796],"category_scores_gemma":[0.05516849,0.0003355358,0.00101101,0.0052237,0.0007591289,0.004257812,0.00319924,0.001205665,0.001916533],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001994652,"about_ca_system_score_gemma":0.001893302,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02185485,"about_ca_topic_score_gemma":0.03572889,"domain_scores_codex":[0.9966223,0.001301516,0.0005080846,0.0005583486,0.0006386279,0.0003710677],"domain_scores_gemma":[0.9558902,0.02752801,0.004928827,0.001195176,0.008966808,0.001490942],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001173536,0.001677282,0.7119804,0.003248474,0.0002196624,0.0006638275,0.1420432,0.0005791296,0.002442544,0.001576664,0.01014408,0.1242512],"study_design_scores_gemma":[0.0000744896,0.0005805119,0.8945643,0.000751776,0.0001481897,0.0001743156,0.08897719,0.004271326,0.0009803596,0.0009443611,0.008438258,0.00009492754],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9650126,0.0002307782,0.003159563,0.0007795005,0.00006169415,0.003619059,0.01799268,0.000134204,0.00901005],"genre_scores_gemma":[0.9487224,0.0004587587,0.02008529,0.0003686631,0.0001133672,0.010694,0.0154937,0.0001029066,0.003960985],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02185485,"threshold_uncertainty_score":0.0434553,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1001435540091303,"score_gpt":0.4699368017855373,"score_spread":0.369793247776407,"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."}}