{"id":"W4394940760","doi":"10.33137/ic.v37i1.42112","title":"Tracking the Trajectories of Genni Gunn’s Writing","year":2023,"lang":"en","type":"article","venue":"Italian Canadiana","topic":"Discourse Analysis in Language Studies","field":"Arts and Humanities","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Tracking (education); Gunn diode; Computer science; Artificial intelligence; Psychology; Engineering; Electrical engineering; Pedagogy","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002323485,0.0001075293,0.0001732548,0.0001430548,0.0004077914,0.0001274422,0.0002295786,0.00001830633,0.001388369],"category_scores_gemma":[0.00008700184,0.00007857278,0.0001182661,0.0001573729,0.0003681583,0.0001286584,0.000025823,0.00007542428,0.00008288794],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004025736,"about_ca_system_score_gemma":0.00005679637,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.03401173,"about_ca_topic_score_gemma":0.3994639,"domain_scores_codex":[0.9991218,0.00002899451,0.0002217456,0.0001398126,0.0001913573,0.0002962259],"domain_scores_gemma":[0.9994417,0.0001010945,0.00007379268,0.0002358344,0.00009293463,0.00005467007],"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":[0.00000305365,0.00001562646,0.002425331,0.00008556997,0.000595792,0.0001278544,0.2223947,0.00007199588,0.00007409952,0.5897853,0.1651899,0.01923081],"study_design_scores_gemma":[0.0001828891,0.00003534305,0.007661878,0.0001251021,0.0002496812,0.000003676454,0.4397565,0.0001587082,0.0003033318,0.003278102,0.5478237,0.0004211548],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5312696,0.002278903,0.00000395248,0.005029352,0.001041899,0.0002071576,0.0003428042,0.0001663081,0.4596601],"genre_scores_gemma":[0.9869779,0.00001626281,0.000006135981,0.0002287604,0.0006542527,0.00001309556,0.00001554467,0.0000189497,0.01206913],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5865072,"threshold_uncertainty_score":0.9995245,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04099069141254256,"score_gpt":0.264845169755673,"score_spread":0.2238544783431305,"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."}}