{"id":"W3022259456","doi":"10.7717/peerj.8962","title":"Origin identification of migratory pests (European Starling) using geochemical fingerprinting","year":2020,"lang":"en","type":"article","venue":"PeerJ","topic":"Isotope Analysis in Ecology","field":"Environmental Science","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia, Okanagan Campus; University of British Columbia; University of Alberta","funders":"Agriculture and Agri-Food Canada; British Columbia Ministry of Agriculture and Lands","keywords":"Starling; Sturnus; Flock; Geography; Population; Ecology; Biology; PEST analysis; Botany","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003469982,0.00006823409,0.0001192462,0.00001824059,0.00004953157,0.00001219814,0.0002147118,0.00002601419,0.0005946393],"category_scores_gemma":[0.0002413161,0.00007301182,0.00005404482,0.0001814325,0.0000936486,0.00008502589,0.0001792972,0.00009320419,0.0003847239],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000617741,"about_ca_system_score_gemma":0.000007013303,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008348499,"about_ca_topic_score_gemma":0.00002044568,"domain_scores_codex":[0.9990925,0.00007287127,0.0002789261,0.0002343593,0.0001789159,0.0001424635],"domain_scores_gemma":[0.9995863,0.00003284218,0.0001506905,0.0001637703,0.00001183262,0.00005460072],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.000003149267,0.00002084461,0.2855423,0.000008007893,0.000008289885,0.000004911503,0.0006260326,0.003439575,0.7089439,0.00001728304,0.0003817125,0.001004026],"study_design_scores_gemma":[0.0003082435,0.00003975575,0.4779189,0.00001323438,0.000109864,0.00000652262,0.0002744714,0.1074015,0.4047448,0.0001759223,0.008641942,0.0003648867],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9960573,0.00001372368,0.001870681,0.0002419508,0.00004542337,0.00005091968,0.000001526108,0.00002572188,0.001692702],"genre_scores_gemma":[0.9975081,0.000002097515,0.002145374,0.0002067281,0.00005719685,0.000001016897,0.000003771381,0.00001037387,0.00006532105],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3041991,"threshold_uncertainty_score":0.6510884,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02532901383922167,"score_gpt":0.2560030793261165,"score_spread":0.2306740654868949,"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."}}