{"id":"W3127763486","doi":"10.1007/s10676-020-09567-7","title":"The CLAIRE COVID-19 initiative: approach, experiences and recommendations","year":2021,"lang":"en","type":"article","venue":"Ethics and Information Technology","topic":"COVID-19 diagnosis using AI","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"Agence Nationale de la Recherche","keywords":"Repurposing; Coronavirus disease 2019 (COVID-19); Pace; Leverage (statistics); Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); 2019-20 coronavirus outbreak; Context (archaeology); Data science; Citizen science; Robotics; Computer science; Artificial intelligence; Engineering ethics; Knowledge management; Engineering; Medicine; Infectious disease (medical specialty); Robot","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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.163585,0.0008954054,0.0007370204,0.002766287,0.01238588,0.03247082,0.005841198,0.01564253,0.02513033],"category_scores_gemma":[0.1405536,0.0004819916,0.001201251,0.002279451,0.01100469,0.01656587,0.0217962,0.02224474,0.005940785],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02571951,"about_ca_system_score_gemma":0.1047465,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05264103,"about_ca_topic_score_gemma":0.09633158,"domain_scores_codex":[0.8849052,0.07806189,0.003618602,0.002139952,0.01813932,0.01313508],"domain_scores_gemma":[0.7253137,0.1197573,0.005426116,0.00506145,0.05650495,0.08793652],"domain_codex":null,"domain_gemma":"evaluation","domain_candidate":"evaluation","domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"qualitative","study_design_scores_codex":[0.0001631179,0.0005314121,0.006185122,0.0007896209,0.00002557406,0.0004771404,0.01334452,0.0002616549,0.0002356926,0.1383557,0.7645854,0.07504509],"study_design_scores_gemma":[0.00008418268,0.00008355394,0.002731593,0.004730397,0.00001672386,0.0004607781,0.06604299,0.0004775117,0.0004310841,0.04245422,0.8823828,0.00010422],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.002776979,0.003562963,0.002215402,0.958541,0.002315083,0.0002366843,0.0002268538,0.00009108082,0.03003401],"genre_scores_gemma":[0.1687088,0.01662842,0.06350544,0.6520033,0.003461899,0.002632987,0.003370164,0.0007671146,0.08892189],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8364149,"threshold_uncertainty_score":0.8651307,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06826673236113259,"score_gpt":0.3800813403468433,"score_spread":0.3118146079857107,"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."}}