{"id":"W4386323007","doi":"10.1016/j.resconrec.2023.107188","title":"Assessing the impact of policy tools on building material recovery","year":2023,"lang":"en","type":"article","venue":"Resources Conservation and Recycling","topic":"Recycled Aggregate Concrete Performance","field":"Engineering","cited_by":20,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Deconstruction (building); Demolition; Demolition waste; Resource recovery; Environmental economics; Resource (disambiguation); Reuse; Computer science; Risk analysis (engineering); Business; Economics; Waste management; Engineering; Civil engineering","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":[],"consensus_categories":[],"category_scores_codex":[0.0003228022,0.0001259446,0.000165222,0.0002086055,0.0001394003,0.0002274014,0.0001070276,0.00007369,0.00001265883],"category_scores_gemma":[0.0002111834,0.00008660336,0.0000689127,0.0004789354,0.00004867869,0.0003064171,0.00003354665,0.0001289865,0.000007363691],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006005146,"about_ca_system_score_gemma":0.00002489115,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001252977,"about_ca_topic_score_gemma":0.000001325529,"domain_scores_codex":[0.999231,0.00004759978,0.000273781,0.000119896,0.0001223401,0.000205358],"domain_scores_gemma":[0.999235,0.000452818,0.00008730403,0.000159017,0.00002653396,0.00003933068],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00009044678,0.000007920613,0.01912709,0.0002569483,0.0001904283,0.00000802604,0.001982094,0.2660502,0.3615268,0.0002970606,0.0009998215,0.3494632],"study_design_scores_gemma":[0.0005768973,0.0001146711,0.343646,0.0008627089,0.0000215671,0.00002483157,0.0005471943,0.610415,0.03860593,0.0004881377,0.004283484,0.0004135695],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.997312,0.00007558018,0.00008341654,0.0003361358,0.000189284,0.0001164026,0.000009558898,0.0002272647,0.001650354],"genre_scores_gemma":[0.9989508,0.0005043201,0.000145505,0.00004585264,0.0002562255,0.000007090133,0.00001128594,0.00002577443,0.00005310506],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3490497,"threshold_uncertainty_score":0.3531582,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03448402654019003,"score_gpt":0.3164192227069431,"score_spread":0.2819351961667531,"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."}}