{"id":"W2109669581","doi":"10.1109/cec.2011.5949656","title":"Evolution of artifact capabilities","year":2011,"lang":"en","type":"article","venue":"","topic":"Language and cultural evolution","field":"Social Sciences","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"Natural Sciences and Engineering Research Council of Canada; National Science Foundation","keywords":"Artifact (error); Computer science; Artificial intelligence; Machine learning; Human–computer interaction","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001827109,0.0003458463,0.0002574417,0.00114214,0.000782307,0.002308901,0.0007952648,0.0008705905,0.003188454],"category_scores_gemma":[0.01339388,0.0003260607,0.0006495162,0.000602452,0.002121961,0.003333247,0.002703518,0.0009043533,0.0003866258],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001302016,"about_ca_system_score_gemma":0.0008669801,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001709113,"about_ca_topic_score_gemma":0.001535188,"domain_scores_codex":[0.998453,0.0007544401,0.00008654506,0.0002701943,0.0002628398,0.0001730403],"domain_scores_gemma":[0.9933124,0.00270987,0.0007383131,0.002048424,0.0007388766,0.0004520452],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0002037408,0.0002724706,0.05856885,0.000258223,0.0002189371,0.002111511,0.007713461,0.1054034,0.03141738,0.6719232,0.001380032,0.1205288],"study_design_scores_gemma":[0.00007959283,0.000798906,0.06600185,0.0002156303,0.0002046724,0.002789075,0.00911191,0.2823428,0.02007002,0.5369229,0.08123821,0.0002244846],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.862025,0.0002478275,0.0921007,0.0007902042,0.00002417621,0.00008571832,0.0001734433,0.0001996187,0.0443534],"genre_scores_gemma":[0.9770985,0.0001100959,0.01957208,0.0000385756,0.000004076531,0.00003591275,0.00009885934,0.00003173475,0.003010147],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003188454,"threshold_uncertainty_score":0.01066649,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03321293051067977,"score_gpt":0.2676773903655215,"score_spread":0.2344644598548417,"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."}}