{"id":"W4200386661","doi":"10.1139/er-2021-0078","title":"Why do we monitor? Using seabird eggs to track trends in Arctic environmental contamination","year":2021,"lang":"en","type":"article","venue":"Environmental Reviews","topic":"Toxic Organic Pollutants Impact","field":"Environmental Science","cited_by":45,"is_retracted":false,"has_abstract":true,"ca_institutions":"Environment and Climate Change Canada; Acadia University; Birds Canada","funders":"","keywords":"Seabird; Arctic; Environmental science; Environmental monitoring; The arctic; Contamination; Ecology; Geography; Oceanography; Biology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":true,"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":["insufficient_payload"],"category_scores_codex":[0.000495705,0.0004651485,0.0005568343,0.0001307219,0.0001393449,0.0000625032,0.0003647269,0.000146025,0.01722388],"category_scores_gemma":[0.00005986313,0.0004640627,0.0002074383,0.000541507,0.0001897313,0.0005393107,0.0003685468,0.0003240071,0.003603618],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003014743,"about_ca_system_score_gemma":0.000008704165,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005597461,"about_ca_topic_score_gemma":0.0001174846,"domain_scores_codex":[0.9965485,0.0003856801,0.000770247,0.0009092466,0.0006746122,0.0007117315],"domain_scores_gemma":[0.9986233,0.00004809044,0.0002063053,0.0007119738,9.134989e-8,0.0004103097],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.00001432357,0.0003858115,0.03768937,0.000005144563,0.00001098224,0.00008786374,0.0007934628,0.00004103671,0.2730993,5.252681e-7,0.0009371449,0.686935],"study_design_scores_gemma":[0.0008792285,0.0001367052,0.6036266,0.0001632837,0.00006223829,0.0001858585,0.0005129036,0.000255611,0.02222202,0.00005419421,0.3711404,0.0007609506],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9868041,0.009654945,0.0002217776,0.001212016,0.0003347106,0.0006722161,0.00008422112,0.00003949156,0.000976547],"genre_scores_gemma":[0.9892977,0.005391895,0.002108977,0.001412006,0.00008854603,0.00003068577,0.00001720783,0.00007328775,0.001579617],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6861741,"threshold_uncertainty_score":0.9997811,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02358188827971211,"score_gpt":0.286389385797042,"score_spread":0.26280749751733,"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."}}