{"id":"W2030919796","doi":"10.1111/j.1936-4490.2004.tb00333.x","title":"Enabling Industrial Ecology through the Forecasting of Durable Goods Disposal: Televisions as an Exemplar Case Study","year":2004,"lang":"en","type":"article","venue":"Canadian Journal of Administrative Sciences / Revue Canadienne des Sciences de l Administration","topic":"Recycling and Waste Management Techniques","field":"Environmental Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Obsolescence; Reuse; Ignorance; Welfare economics; Economy; Environmental economics; Engineering; Economics; Business; Law; Political science; Waste management; Marketing","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.001699733,0.0005468047,0.0004060603,0.001646942,0.000951057,0.002429665,0.001225195,0.002190968,0.00240429],"category_scores_gemma":[0.003148505,0.0003173178,0.0009849966,0.00239683,0.0009870944,0.00136891,0.001213104,0.001063585,0.0002663354],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002289692,"about_ca_system_score_gemma":0.001522619,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03802476,"about_ca_topic_score_gemma":0.03515152,"domain_scores_codex":[0.9989603,0.0005360233,0.00005039305,0.000111318,0.0002176073,0.000124468],"domain_scores_gemma":[0.9967346,0.002452624,0.0001792383,0.0002229193,0.0003047167,0.0001059172],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.000239082,0.0004905546,0.05188198,0.0002052119,0.00008836245,0.003819352,0.001218698,0.8956826,0.002689146,0.00901041,0.001302973,0.03337159],"study_design_scores_gemma":[0.00004286279,0.0002911963,0.01091325,0.00007203436,0.00005916571,0.0002191485,0.003831288,0.967284,0.004970488,0.005593215,0.00666604,0.00005734422],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9622467,0.0002724503,0.0236849,0.0007829857,0.00002600479,0.0001980217,0.0006487983,0.0001657049,0.01197435],"genre_scores_gemma":[0.9800364,0.0002916674,0.01701221,0.00002412841,0.00001106117,0.00005654338,0.0002702464,0.00001977802,0.002277995],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03802476,"threshold_uncertainty_score":0.07560682,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1677437703999761,"score_gpt":0.3516794971507383,"score_spread":0.1839357267507622,"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."}}