{"id":"W2322984202","doi":"10.1177/0013916515577635","title":"Trash or Recycle? How Product Distortion Leads to Categorization Error During Disposal","year":2015,"lang":"en","type":"article","venue":"Environment and Behavior","topic":"Environmental Education and Sustainability","field":"Environmental Science","cited_by":42,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Categorization; Product (mathematics); Distortion (music); Signage; Architectural engineering; Computer science; Business; Engineering; Advertising; Artificial intelligence; Mathematics; Telecommunications","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":[0.02628461,0.0004858011,0.0007034664,0.001287838,0.001368154,0.004754561,0.001737914,0.002172142,0.005791034],"category_scores_gemma":[0.2074638,0.0007836448,0.0009657306,0.001082642,0.003230127,0.005604325,0.002548615,0.002290431,0.001193714],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002010993,"about_ca_system_score_gemma":0.001973778,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01610616,"about_ca_topic_score_gemma":0.008872236,"domain_scores_codex":[0.9762377,0.01094313,0.001558905,0.003249338,0.006899881,0.00111116],"domain_scores_gemma":[0.8370972,0.1010321,0.02886632,0.01535366,0.01624113,0.001409697],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001599562,0.00120856,0.6233288,0.0008572564,0.0004679702,0.001171407,0.07924754,0.002900072,0.008498121,0.01313566,0.008878999,0.2587061],"study_design_scores_gemma":[0.0002712251,0.0007967402,0.7899828,0.00150699,0.0007756703,0.002620805,0.065153,0.03275852,0.01548772,0.06531908,0.02476231,0.0005651065],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9578642,0.0009269874,0.01816323,0.005574032,0.0002251652,0.0002002192,0.0001265558,0.000180216,0.01673935],"genre_scores_gemma":[0.9899588,0.0003838373,0.005972917,0.001204734,0.00006842204,0.00006473278,0.0001331612,0.0001072964,0.00210599],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02628461,"threshold_uncertainty_score":0.1390079,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02119568076531747,"score_gpt":0.2578696938354393,"score_spread":0.2366740130701218,"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."}}