{"id":"W3042452225","doi":"10.1177/0003702820946033","title":"Steps Scientists Can Take to Inform Aquatic Microplastics Management: A Perspective Informed by the California Experience","year":2020,"lang":"en","type":"article","venue":"Applied Spectroscopy","topic":"Microplastics and Plastic Pollution","field":"Environmental Science","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Microplastics; Perspective (graphical); Environmental planning; Legislature; Environmental resource management; Risk management; Business; Engineering ethics; Environmental science; Political science; Engineering; Computer science; Ecology","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":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0001042908,0.0002632482,0.0001854869,0.00003959633,0.0004810086,0.0001556795,0.0005484243,0.00005418385,0.0009668551],"category_scores_gemma":[0.00007719983,0.000203929,0.00004340762,0.0008543694,0.0003052592,0.00007209728,0.0003517521,0.0002001952,0.002990574],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005162482,"about_ca_system_score_gemma":0.00003635821,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002384353,"about_ca_topic_score_gemma":0.000365951,"domain_scores_codex":[0.998076,0.00001230945,0.0002997377,0.0004679306,0.0005430998,0.0006009866],"domain_scores_gemma":[0.999159,0.0000835695,0.0001094043,0.0002914666,0.000008778286,0.0003477296],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0004917601,0.0001921642,0.001956522,0.00006262302,0.0001110067,0.00002824585,0.03728212,0.002143424,0.7243345,0.03848494,0.1920285,0.002884176],"study_design_scores_gemma":[0.003235759,0.00080457,0.007599051,0.00006255642,0.0002126059,0.00003897325,0.0200174,0.01115542,0.266884,0.002743324,0.6851172,0.002129126],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7170935,0.00003935148,0.1377088,0.005103157,0.0004470421,0.002388094,0.0005553177,0.0002008636,0.1364639],"genre_scores_gemma":[0.9905628,0.00001306761,0.005590423,0.003313819,0.0000518277,0.00008577552,0.00002282127,0.0000216964,0.0003377957],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4930888,"threshold_uncertainty_score":0.9999464,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008610167624325578,"score_gpt":0.2300192008743456,"score_spread":0.22140903325002,"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."}}