{"id":"W2946288588","doi":"10.1515/css-2019-0013","title":"AI: A Semiotic Perspective","year":2019,"lang":"en","type":"article","venue":"Chinese Semiotic Studies","topic":"Cognitive Science and Education Research","field":"Neuroscience","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Toronto Metropolitan University","funders":"","keywords":"Semiotics; Semiosis; Cognitive science; Cognition; Meaning (existential); Epistemology; Posthumanism; Human intelligence; Context (archaeology); Perception; Sociology; Psychology; Computer science; Artificial intelligence; Philosophy","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0003484417,0.0001939701,0.0002907423,0.0001916746,0.0002785382,0.00006792776,0.0003448123,0.00003379869,0.0004921872],"category_scores_gemma":[0.008119831,0.0001333353,0.00009471067,0.001120706,0.000379317,0.000264233,0.0002585969,0.0002533063,0.00284125],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001707085,"about_ca_system_score_gemma":0.0001342658,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002658679,"about_ca_topic_score_gemma":0.00001003181,"domain_scores_codex":[0.9980964,0.0001282827,0.0001819303,0.0006461781,0.000488189,0.0004590222],"domain_scores_gemma":[0.9978334,0.001289494,0.00005251206,0.0003456273,0.0003672262,0.0001117259],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001886289,0.001058074,0.4491348,0.0004753183,0.0002358177,0.0001200268,0.09217644,0.0002527595,0.3628718,0.04097066,0.04696498,0.005550764],"study_design_scores_gemma":[0.004345351,0.001266954,0.4776381,0.0007650678,0.0001167056,0.0003042327,0.1865354,0.006272088,0.1066724,0.205948,0.007282989,0.002852798],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9571674,0.0007801751,0.0000156055,0.01009649,0.001145234,0.0004020233,0.000004914776,0.00008670795,0.03030138],"genre_scores_gemma":[0.985311,0.0002650778,0.00002608209,0.003660073,0.0001771022,0.00002055556,4.591896e-7,0.00001391323,0.01052572],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2561994,"threshold_uncertainty_score":0.9979352,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07651351944410499,"score_gpt":0.4450556693637123,"score_spread":0.3685421499196073,"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."}}