{"id":"W2790658138","doi":"10.1016/j.wasman.2018.03.030","title":"Toward zero waste events: Reducing contamination in waste streams with volunteer assistance","year":2018,"lang":"en","type":"article","venue":"Waste Management","topic":"Municipal Solid Waste Management","field":"Environmental Science","cited_by":43,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Garbage; Bin; Contamination; Waste management; STREAMS; Municipal solid waste; Environmental science; Volunteer; Zero waste; Engineering; Computer science; Ecology","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0007341146,0.000424407,0.0003421874,0.000221303,0.0001830853,0.0000931674,0.0007648693,0.00007341652,0.0009121462],"category_scores_gemma":[0.00001455424,0.0003848443,0.00007205913,0.000877485,0.000245915,0.0005024157,0.001099618,0.0002004018,0.0006346109],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009709896,"about_ca_system_score_gemma":0.000006771744,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007020322,"about_ca_topic_score_gemma":0.001359753,"domain_scores_codex":[0.9964206,0.0001421523,0.0005818927,0.0009836039,0.001028999,0.0008427018],"domain_scores_gemma":[0.9985431,0.0000250645,0.0002662412,0.0009800799,0.00002623395,0.0001593181],"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":[0.001387376,0.002371477,0.05205322,0.0009878788,0.0008459569,0.0008138646,0.01434442,0.5938771,0.0008745887,0.0109916,0.0417388,0.2797137],"study_design_scores_gemma":[0.02084416,0.004287711,0.07274022,0.0043731,0.0009081214,0.00003932748,0.08371602,0.6060013,0.01133951,0.003336522,0.1859853,0.006428657],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8007993,0.000038971,0.01340637,0.0006839007,0.0004499797,0.001585014,0.000006684796,0.0000881376,0.1829416],"genre_scores_gemma":[0.978541,0.00003427414,0.002300751,0.0003509911,0.0001276231,0.0001701492,0.00001826487,0.0000585921,0.01839835],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2732851,"threshold_uncertainty_score":0.9998603,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01266955932205378,"score_gpt":0.2282832015249547,"score_spread":0.2156136422029009,"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."}}