{"id":"W3035808935","doi":"10.24908/ss.v18i2.13937","title":"Wearables and Sur(over)-Veillance, Sous(under)-Veillance, Co(So)-Veillance, and MetaVeillance (Veillance of Veillance) for Health and Well-Being","year":2020,"lang":"en","type":"article","venue":"Surveillance & Society","topic":"Ethics in medical practice","field":"Health Professions","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Grassroots; Duty; Open source; Big data; Passion; Computer science; Big business; Internet privacy; Sociology; Law; Political science; Psychology; Social psychology","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":["sts"],"consensus_categories":[],"category_scores_codex":[0.005614462,0.001615304,0.0007060529,0.001466756,0.007220404,0.0202754,0.001267793,0.005061809,0.01669318],"category_scores_gemma":[0.008659339,0.0007970132,0.0007421103,0.001383452,0.02639036,0.01779398,0.01193886,0.006612319,0.004148723],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0070694,"about_ca_system_score_gemma":0.005393974,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04058241,"about_ca_topic_score_gemma":0.06253592,"domain_scores_codex":[0.9947536,0.002366535,0.0002157532,0.0007166884,0.001328465,0.000618931],"domain_scores_gemma":[0.9903296,0.002913841,0.0006329222,0.001383979,0.001459385,0.00328024],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001747971,0.00004950086,0.003911953,0.0007905721,0.00005806908,0.0002499613,0.03628805,0.0006059195,0.002168212,0.5715186,0.2387197,0.1454646],"study_design_scores_gemma":[0.00001711926,0.0001124004,0.003112356,0.0006396832,0.00002716735,0.0005281651,0.01695089,0.0007994839,0.00106521,0.08506513,0.89155,0.0001324625],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.03917601,0.08928661,0.1262075,0.3486234,0.0210866,0.0001970634,0.0010172,0.003943341,0.3704623],"genre_scores_gemma":[0.704099,0.05092874,0.04771993,0.03822972,0.008034569,0.0002596446,0.0008438303,0.001934541,0.1479499],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9927796,"threshold_uncertainty_score":0.08069241,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03854641318917131,"score_gpt":0.4038687414275207,"score_spread":0.3653223282383494,"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."}}