{"id":"W6889754268","doi":"10.26071/222629b6-c7a2-4580","title":"Profiling Accumulated PAHs and Metabolomic Responses in Truncate Soft-Shell Clam (Mya truncata) in the Canadian Arctic","year":2025,"lang":"en","type":"dataset","venue":"OGSL repository","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"","keywords":"Arctic; Ecosystem; Shellfish; Contamination; Ruditapes; The arctic; Oyster; Pollution; Inlet","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0007495554,0.001094024,0.0008626041,0.002853012,0.001612908,0.001238237,0.001531601,0.0007059366,0.004037681],"category_scores_gemma":[0.001721801,0.0003266917,0.0007895552,0.00599277,0.0003891246,0.0003122289,0.001447242,0.0006415977,0.002337947],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00636042,"about_ca_system_score_gemma":0.0101441,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8837719,"about_ca_topic_score_gemma":0.9486745,"domain_scores_codex":[0.9994113,0.0000333849,0.00003646381,0.0001884877,0.0001916018,0.0001388143],"domain_scores_gemma":[0.9986727,0.0001053082,0.0001216019,0.0001215412,0.0008282631,0.0001506114],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001418813,0.0001745951,0.234807,0.004908961,0.001384696,0.0005151108,0.001122036,0.006305275,0.01334564,0.002207839,0.6873423,0.04646767],"study_design_scores_gemma":[0.0001512779,0.00005628692,0.4855548,0.0007534957,0.0003514004,0.000191632,0.000850175,0.001652453,0.003211726,0.0006866344,0.5064063,0.0001338339],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.01016973,0.00042194,0.0001272947,0.00007253768,0.00001150022,0.00001449423,0.988167,0.0001093645,0.0009060948],"genre_scores_gemma":[0.009349635,0.0002601325,0.0005680632,0.00004732217,0.000002640929,0.00004197196,0.9890132,0.00002024997,0.0006967696],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1162281,"threshold_uncertainty_score":0.2338251,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02081960927467454,"score_gpt":0.2854010963219497,"score_spread":0.2645814870472751,"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."}}