{"id":"W4411180546","doi":"10.5325/tpnc.2.1.0077","title":"Short Papers from Interpolations 2","year":2025,"lang":"en","type":"article","venue":"Theatre and Performance Notes and Counternotes","topic":"Innovative Human-Technology Interaction","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science","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":[0.0000715937,0.0001184218,0.0001194498,0.0001251957,0.0001959515,0.0001209227,0.0002055751,0.00006818925,0.00001611785],"category_scores_gemma":[0.000007173951,0.00009913369,0.00001824964,0.0001552616,0.0001016012,0.0004427029,0.0001544046,0.0001536387,0.000007821684],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001700815,"about_ca_system_score_gemma":0.00001339108,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000952314,"about_ca_topic_score_gemma":0.00005437344,"domain_scores_codex":[0.9993988,0.00001137351,0.0001435692,0.0002425371,0.00006622761,0.0001375259],"domain_scores_gemma":[0.9995613,0.0001300441,0.00002715451,0.0002208451,0.00004329511,0.00001734217],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.00002983524,0.0000237997,0.2146589,0.0000199016,0.00006276472,0.000001640714,0.0008626767,0.000003614042,0.00381669,0.01892025,0.00009881281,0.7615011],"study_design_scores_gemma":[0.0007602152,0.0004394704,0.77664,0.0006188899,0.000069501,0.00003752892,0.0004512311,0.1385626,0.03195249,0.02069036,0.02908054,0.0006971648],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9705413,0.0004064445,0.01913048,0.001451396,0.0002420308,0.00006985934,0.000005593538,0.0001132985,0.008039608],"genre_scores_gemma":[0.9980871,0.0003130127,0.000802653,0.0006190287,0.00003618309,0.00001007396,0.00000547309,0.000003678842,0.0001227874],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7608039,"threshold_uncertainty_score":0.4042554,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009119502431028605,"score_gpt":0.2489764116410234,"score_spread":0.2398569092099948,"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."}}