{"id":"W2749091255","doi":"10.37693/pjos.2017.8.16686","title":"Learning that Reflects the Living: Aligning Anticipation and Edusemiotics","year":2017,"lang":"en","type":"article","venue":"Public Journal of Semiotics","topic":"Education Methods and Practices","field":"Social Sciences","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Semiosis; Epistemology; Biosemiotics; Reductionism; Living systems; Anticipation (artificial intelligence); Cognitive science; Sign (mathematics); Sociology; Psychology; Semiotics; Computer science; Philosophy; Artificial intelligence","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","sts","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.01000486,0.00007044344,0.0001429589,0.00007588674,0.002479618,0.001430486,0.0004692241,0.0000774182,0.00004037033],"category_scores_gemma":[0.028,0.00005016528,0.00004446914,0.00008528759,0.0002831164,0.001267402,0.00007342701,0.0004577322,0.000001868775],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004433142,"about_ca_system_score_gemma":0.000347769,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001112995,"about_ca_topic_score_gemma":0.00009431128,"domain_scores_codex":[0.9981766,0.0008407571,0.0002462611,0.00008004977,0.0004259944,0.0002303506],"domain_scores_gemma":[0.9953629,0.002604115,0.001299706,0.0001779755,0.0004014089,0.0001539289],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000007305342,0.00007549197,0.8183454,0.00002444007,0.00008725541,0.000005064438,0.07439999,0.00004068081,0.0002250739,0.03583264,0.002097213,0.06885944],"study_design_scores_gemma":[0.0003424591,0.0002456508,0.2764639,0.000414066,0.0002498892,0.00009020038,0.1449002,0.0005848233,0.0003255172,0.01058741,0.5654241,0.0003718141],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8536608,0.001113639,0.003962285,0.1039492,0.002168813,0.0001129503,3.821745e-7,0.00001977989,0.03501219],"genre_scores_gemma":[0.9866533,0.002906878,0.008572169,0.0002372463,0.0009025589,2.860012e-7,1.331485e-7,0.000008297114,0.0007190948],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5633269,"threshold_uncertainty_score":0.9996061,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2075296344788225,"score_gpt":0.4704220691997565,"score_spread":0.262892434720934,"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."}}