{"id":"W4403619675","doi":"10.1007/s43681-024-00594-4","title":"Lifecycles, pipelines, and value chains: toward a focus on events in responsible artificial intelligence for health","year":2024,"lang":"en","type":"article","venue":"AI and Ethics","topic":"Ethics and Social Impacts of AI","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Health Sciences Centre; Sunnybrook Health Science Centre; Public Health Ontario; University of Toronto","funders":"","keywords":"Focus (optics); Value (mathematics); Pipeline transport; Computer science; Business; Artificial intelligence; Engineering; Machine learning; Physics; Mechanical engineering","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":["sts"],"consensus_categories":[],"category_scores_codex":[0.01558166,0.0006558082,0.0005062107,0.002746979,0.003780792,0.01426422,0.001928409,0.005454746,0.006522508],"category_scores_gemma":[0.02412951,0.0008475984,0.0008240819,0.002639146,0.04566805,0.03503378,0.006995629,0.00574267,0.0005363827],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006941859,"about_ca_system_score_gemma":0.0107482,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007856379,"about_ca_topic_score_gemma":0.005497997,"domain_scores_codex":[0.9931698,0.004638643,0.0002455665,0.0005858351,0.0008113543,0.0005487747],"domain_scores_gemma":[0.9784984,0.01375077,0.001938067,0.002580569,0.001452942,0.001779209],"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":[0.000005718874,0.000008176119,0.0003028181,0.00001821141,0.000002142384,0.00001928615,0.0007713573,0.0004235488,0.00002935115,0.9949465,0.0006211564,0.00285174],"study_design_scores_gemma":[0.000003594421,0.000004690128,0.00009767393,0.00004747376,0.000002583196,0.00002218442,0.0008417904,0.001187441,0.00007498739,0.9887697,0.008942974,0.000004952157],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05055689,0.00691657,0.5956015,0.1842849,0.0005546485,0.0003450505,0.0003283427,0.0003172216,0.1610949],"genre_scores_gemma":[0.8972047,0.004474903,0.08210873,0.003831798,0.0004529819,0.0003092943,0.0001217478,0.0001983151,0.01129768],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9962192,"threshold_uncertainty_score":0.08240461,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1841903427887943,"score_gpt":0.4854000962914256,"score_spread":0.3012097535026313,"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."}}