{"id":"W2055815627","doi":"10.1111/j.1530-9290.2008.00041.x","title":"Identifying and Predicting Biological Risks Associated With Manufactured Nanoparticles in Aquatic Ecosystems","year":2008,"lang":"en","type":"article","venue":"Journal of Industrial Ecology","topic":"Nanoparticles: synthesis and applications","field":"Materials Science","cited_by":52,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; Killam Trusts","keywords":"Aquatic ecosystem; Microplastics; Environmental science; Biochemical engineering; Ecotoxicity; Environmental chemistry; Ecosystem; Pollutant; Aquatic toxicology; Bioavailability; Risk analysis (engineering); Chemistry; Ecology; Business; Toxicity; Biology; Engineering","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005637468,0.0004667121,0.0003815892,0.00089174,0.0003105321,0.0006565505,0.0002832626,0.001199108,0.0004485169],"category_scores_gemma":[0.001382664,0.0002660681,0.0005559426,0.0003040246,0.0002691259,0.0003997773,0.0004216133,0.0003510756,0.0001561413],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006395513,"about_ca_system_score_gemma":0.0004273138,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003475442,"about_ca_topic_score_gemma":0.004052103,"domain_scores_codex":[0.9996232,0.0001053334,0.00002394368,0.00007865182,0.0001229562,0.0000459053],"domain_scores_gemma":[0.9991418,0.0005248851,0.0001820324,0.00002713565,0.00009515727,0.00002904234],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001062382,0.0003770596,0.4475233,0.0003117791,0.0003091576,0.0006211802,0.0001548888,0.1899541,0.307062,0.0008608481,0.0002519006,0.05151141],"study_design_scores_gemma":[0.00004513881,0.002502677,0.2540001,0.00003801536,0.0003322959,0.0006638133,0.0007478605,0.4632287,0.2725784,0.004352829,0.001447224,0.00006299373],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9956559,0.00008451398,0.003561122,0.00002797176,0.00000318964,0.00001739652,0.00008689681,0.00001293689,0.0005501846],"genre_scores_gemma":[0.9961376,0.0001748482,0.00305036,0.00001542535,0.000002250101,0.00002086483,0.0001119596,0.000003258452,0.0004835628],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003475442,"threshold_uncertainty_score":0.006910384,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1358827882085876,"score_gpt":0.2924414880807535,"score_spread":0.1565586998721659,"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."}}