{"id":"W191669756","doi":"10.1023/a:1025517007605","title":"Metal Contamination in Zebra Mussels (Dreissena Polymorpha) Along the st. Lawrence River","year":2003,"lang":"en","type":"article","venue":"Environmental Monitoring and Assessment","topic":"Heavy metals in environment","field":"Environmental Science","cited_by":73,"is_retracted":false,"has_abstract":false,"ca_institutions":"GDG Environnement; McGill University","funders":"National Research Council Canada","keywords":"Dreissena; Bioaccumulation; Zebra mussel; Environmental science; Contamination; Environmental chemistry; Ecotoxicology; Bivalvia; Seasonality; Pollution; Bioconcentration; Mussel; Ecology; Mollusca; Biology; Chemistry","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","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0009359618,0.0003167905,0.0002431946,0.00004570346,0.000303498,0.00005647944,0.0002511526,0.00009291758,0.0009971639],"category_scores_gemma":[0.00002281101,0.0002549345,0.00006713053,0.0001354258,0.0005297046,0.0003979979,0.0002576307,0.0003976536,0.0001384049],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007215224,"about_ca_system_score_gemma":0.00001023878,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002655299,"about_ca_topic_score_gemma":0.00002128281,"domain_scores_codex":[0.997412,0.0003587345,0.0003993011,0.0006068804,0.0007168407,0.0005062128],"domain_scores_gemma":[0.9991416,0.0001546272,0.0001274962,0.0004136822,7.941109e-7,0.0001617678],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000005088332,0.0003071351,0.9456519,0.000004719698,0.00002302668,0.00003353481,0.000573715,0.0006027844,0.03358765,0.0002392378,0.00003418319,0.01893703],"study_design_scores_gemma":[0.0005785337,0.00008836282,0.9685819,0.0000237925,0.00002901149,0.00002531294,0.001107426,0.0001520935,0.02034667,0.0002200197,0.008535765,0.0003110817],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9946575,0.0003776747,0.0002913512,0.0001824806,0.0004150613,0.0004387543,0.000009245181,0.00002559179,0.003602325],"genre_scores_gemma":[0.9955748,0.0003994969,0.003111894,0.00006380172,0.00006261538,0.0001145542,0.00000680875,0.00003156599,0.0006344107],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02293004,"threshold_uncertainty_score":0.9999903,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01318542148762268,"score_gpt":0.2586813827390232,"score_spread":0.2454959612514005,"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."}}