{"id":"W7034188485","doi":"","title":"Toxicity of Microplastics and Nanoplastics to Model Aquatic Organism, Daphnia magna","year":2023,"lang":"en","type":"dissertation","venue":"eScholarship@McGill (McGill)","topic":"Prenatal Screening and Diagnostics","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Fonds de recherche du Québec – Nature et technologies; Natural Sciences and Engineering Research Council of Canada; Fisheries and Oceans Canada; Mitacs; Environment and Climate Change Canada; McGill University; Killam Trusts; Canada Research Chairs","keywords":"Microplastics; Daphnia magna; Toxicity; Aquatic toxicology; Aquatic ecosystem; Aquatic environment","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007374294,0.0001346698,0.0001064322,0.0001209012,0.0001983863,0.0002037222,0.00005967671,0.0002391313,0.001721732],"category_scores_gemma":[0.00009228216,0.00007004535,0.0001727803,0.00009535807,0.0000815743,0.00008147985,0.0001511503,0.0002658541,0.0002637385],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002548973,"about_ca_system_score_gemma":0.0003186539,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002170431,"about_ca_topic_score_gemma":0.005928399,"domain_scores_codex":[0.9999626,0.000003401913,0.000003327859,0.000009437953,0.0000146043,0.000006639118],"domain_scores_gemma":[0.9999518,0.00001094699,0.000008816226,0.000002704247,0.00001601689,0.000009756235],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001575255,0.0000834675,0.00280382,0.0005494888,0.00002702376,0.0001936351,0.0001729597,0.0008250959,0.9734899,0.0002385797,0.002176345,0.01928221],"study_design_scores_gemma":[0.00004751883,0.002983063,0.06799553,0.0001769179,0.0001388061,0.0005990589,0.0007564059,0.001689793,0.8859807,0.0004735179,0.03912336,0.00003525599],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9766948,0.006954235,0.0008587092,0.001058155,0.0001731433,0.00005079668,0.001487158,0.00002129288,0.01270165],"genre_scores_gemma":[0.9428297,0.009039737,0.002662324,0.0006034155,0.0000343625,0.00007358677,0.00160068,0.00001232381,0.04314379],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002170431,"threshold_uncertainty_score":0.005759776,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01837803613931747,"score_gpt":0.253400943473383,"score_spread":0.2350229073340655,"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."}}