{"id":"W2895973392","doi":"10.1109/cig.2018.8490374","title":"Evolving Number Sentence Morphing Puzzles","year":2018,"lang":"en","type":"article","venue":"","topic":"Artificial Intelligence in Games","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Sentence; Computer science; Morphing; Class (philosophy); Edit distance; Artificial intelligence; Word (group theory); Object (grammar); Natural language processing; Theoretical computer science; Mathematics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004650873,0.0006901858,0.0005253272,0.0005876189,0.0004828454,0.0008084741,0.00116185,0.0009521192,0.005787776],"category_scores_gemma":[0.004024557,0.0003437557,0.0007840475,0.0003274931,0.0006504355,0.001279996,0.001361864,0.0007650778,0.0004737667],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000636347,"about_ca_system_score_gemma":0.0003748612,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001167371,"about_ca_topic_score_gemma":0.0013158,"domain_scores_codex":[0.9997765,0.00007018973,0.00001582694,0.00006374206,0.00004305245,0.00003064181],"domain_scores_gemma":[0.9991763,0.0004982316,0.0000677758,0.00008764034,0.00009712872,0.00007298593],"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":[0.0004038577,0.0004799784,0.007258432,0.0004126735,0.0001499232,0.001316236,0.00194843,0.6563091,0.03348327,0.1461708,0.006387115,0.1456802],"study_design_scores_gemma":[0.00007935117,0.0001947655,0.001026667,0.00003163381,0.00004112242,0.0002562973,0.0002543057,0.93738,0.004133771,0.04689813,0.009672499,0.00003141465],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6188715,0.0003712543,0.35003,0.000613357,0.0001615863,0.0003351422,0.0004147079,0.0009421828,0.02826026],"genre_scores_gemma":[0.7411237,0.0002140528,0.2456363,0.0001739289,0.00002444815,0.0003389901,0.0008164922,0.0002373765,0.01143469],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005787776,"threshold_uncertainty_score":0.01936209,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03646522643798296,"score_gpt":0.30391587003812,"score_spread":0.2674506436001371,"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."}}