{"id":"W4389124706","doi":"10.2139/ssrn.4629424","title":"Framing cognitive machines: A sociotechnical taxonomy","year":2023,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Innovation, Sustainability, Human-Machine Systems","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université du Québec à Trois-Rivières","funders":"","keywords":"Sociotechnical system; Categorization; Taxonomy (biology); Framing (construction); Management science; Cybernetics; Computer science; Data science; Knowledge management; Cognition; Epistemology; Sociology; Artificial intelligence; Engineering; Psychology; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.004913953,0.001071744,0.0005781306,0.007341433,0.002934658,0.01139132,0.001984136,0.003490441,0.006939371],"category_scores_gemma":[0.01131097,0.0007477661,0.001031814,0.004622112,0.01502493,0.0157846,0.003223579,0.002314278,0.0008080027],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002954205,"about_ca_system_score_gemma":0.002741583,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002857913,"about_ca_topic_score_gemma":0.002057162,"domain_scores_codex":[0.9964386,0.002189308,0.0002360826,0.0003725445,0.000503419,0.0002600926],"domain_scores_gemma":[0.9904032,0.006580983,0.0008146401,0.0009671762,0.0008211673,0.0004129134],"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":[0.000004274381,0.00001390113,0.0005519205,0.00003025234,0.000004280949,0.00003828666,0.002713903,0.0004302315,0.0001011326,0.991087,0.0002658609,0.004758893],"study_design_scores_gemma":[0.000009487847,0.00001505466,0.0005610002,0.00008760489,0.000008606827,0.0001272081,0.003334516,0.004556852,0.0001414386,0.9810171,0.01012816,0.00001297953],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06562557,0.003687652,0.7176487,0.01318695,0.0002341345,0.0003967337,0.0003203638,0.0002587369,0.1986411],"genre_scores_gemma":[0.8090555,0.002648739,0.1803794,0.0004910277,0.0002104229,0.0006625167,0.0002963748,0.00007425343,0.006181735],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9970654,"threshold_uncertainty_score":0.0259878,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02479195766851384,"score_gpt":0.3339994261006872,"score_spread":0.3092074684321734,"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."}}