{"id":"W1509525110","doi":"10.1007/978-3-540-70569-7_28","title":"Task Model Refinement with Meta Operators","year":2008,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Usability and User Interface Design","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":false,"ca_institutions":"Concordia University","funders":"","keywords":"Computer science; Equivalence (formal languages); Task (project management); Model transformation; Transformation (genetics); Software engineering; Programming language; User interface; Relation (database); Data mining; Systems engineering; Artificial intelligence","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00074309,0.0007328571,0.0008229039,0.0005825916,0.0003340618,0.0004947765,0.004403271,0.0002832396,0.00003614379],"category_scores_gemma":[0.00003639519,0.0005349684,0.0002023991,0.0005842828,0.0008930149,0.0007900997,0.001247676,0.0008847127,0.00006642989],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003204636,"about_ca_system_score_gemma":0.001005571,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003116122,"about_ca_topic_score_gemma":0.0001278311,"domain_scores_codex":[0.9952369,0.00004325106,0.0005554844,0.002064714,0.001362497,0.0007371591],"domain_scores_gemma":[0.9967235,0.0002092402,0.0002172721,0.002257973,0.0003578683,0.0002341851],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002481698,0.0001185757,0.0000212103,0.00005329305,0.0002258683,0.0002292162,0.002543564,0.8545764,0.0001430707,0.01691709,0.0004468798,0.1247],"study_design_scores_gemma":[0.0002978005,0.0003903849,0.000008530528,0.0001466553,0.00007076118,0.0001308052,9.59883e-8,0.9642776,0.002371147,0.02709469,0.004251596,0.0009599892],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0001267992,0.0007644032,0.994266,0.001464735,0.000480125,0.0004400701,0.000008387777,0.0001934326,0.002256087],"genre_scores_gemma":[0.1107756,0.0001510576,0.8836445,0.004186305,0.0001656983,0.00003800771,0.000004155518,0.00005511595,0.0009795931],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.12374,"threshold_uncertainty_score":0.9997102,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04236297868629113,"score_gpt":0.2460049387594697,"score_spread":0.2036419600731786,"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."}}