{"id":"W4396910770","doi":"10.1109/ieeeconf58110.2023.10520570","title":"Framing Cognitive Machines: A Sociotechnical Taxonomy","year":2023,"lang":"en","type":"article","venue":"","topic":"Innovation, Sustainability, Human-Machine Systems","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Trois-Rivières","funders":"Agence Nationale de la Recherche","keywords":"Sociotechnical system; Taxonomy (biology); Categorization; Framing (construction); Computer science; Cybernetics; Management science; Data science; Knowledge management; Artificial intelligence; Engineering; Ecology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002587079,0.0001289675,0.0001882404,0.000208294,0.001017123,0.0001204163,0.0002641423,0.000182077,0.0006184712],"category_scores_gemma":[0.002379124,0.0001221862,0.00008986664,0.00142328,0.00041933,0.000263697,0.0001103374,0.0002652855,0.0004235937],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002641105,"about_ca_system_score_gemma":0.0004018677,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007575213,"about_ca_topic_score_gemma":0.003863422,"domain_scores_codex":[0.9980525,0.0003356956,0.0003356321,0.0003223849,0.0004699098,0.0004838391],"domain_scores_gemma":[0.9986334,0.0005973376,0.00009519057,0.0001693962,0.000423985,0.00008070974],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001773527,0.0001256785,0.08816718,0.0001202971,0.00006601707,0.00003040316,0.04282221,0.00002053635,0.00004814616,0.8256059,0.01924465,0.02373128],"study_design_scores_gemma":[0.001281798,0.0001360584,0.07008894,0.0001221115,0.00005105784,0.000003719523,0.3850728,0.003341524,0.00007436534,0.08108826,0.4575002,0.001239181],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5460491,0.00003779436,0.01777801,0.007259062,0.0008664241,0.002614299,0.00001422125,0.002710678,0.4226705],"genre_scores_gemma":[0.9885585,0.000004006167,0.0002476364,0.0002913498,0.0005723664,0.0002386516,0.00002395905,0.00001749224,0.01004609],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7445176,"threshold_uncertainty_score":0.9990335,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05600044801622957,"score_gpt":0.3712243358188735,"score_spread":0.315223887802644,"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."}}