{"id":"W2526087556","doi":"10.32747/2016.7208739.ws","title":"Geese, Ducks and Coots","year":2016,"lang":"en","type":"report","venue":"","topic":"Wildlife Conservation and Criminology Analyses","field":"Environmental Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Goose; Waterfowl; Anatidae; Cormorant; Vegetation (pathology); Branta; Snow; Geography; Nest (protein structural motif); Agriculture; Ecology; Biology; Fishery; Habitat; Predation","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0004596094,0.000455731,0.0001163728,0.001354109,0.001329932,0.0008817964,0.0003195212,0.0002790486,0.02004144],"category_scores_gemma":[0.0008868183,0.0001663894,0.0001695315,0.001134719,0.0002869859,0.0004188606,0.0007502424,0.0003783271,0.007658355],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001079909,"about_ca_system_score_gemma":0.004054852,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.3719565,"about_ca_topic_score_gemma":0.6930695,"domain_scores_codex":[0.9987844,0.00006106574,0.00004360728,0.0001031311,0.0007692277,0.0002385689],"domain_scores_gemma":[0.9986315,0.00008724691,0.0001216472,0.00008323127,0.0008286666,0.0002476228],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.0001406051,0.0003538849,0.1356046,0.0003941506,0.00003648798,0.00072007,0.002037732,0.0002020337,0.002921668,0.004847435,0.5767028,0.2760385],"study_design_scores_gemma":[0.00001203155,0.0001243647,0.203182,0.000187844,0.00001333191,0.0005437624,0.002550606,0.0001029449,0.001269281,0.0002055398,0.7917937,0.00001462549],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.1546923,0.001527625,0.000968434,0.001438566,0.0002770542,0.00092034,0.03914956,0.0003146111,0.8007115],"genre_scores_gemma":[0.144808,0.005023936,0.002411933,0.001678268,0.00008712044,0.0004170892,0.04336039,0.00007809694,0.8021352],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.3719565,"threshold_uncertainty_score":0.7395829,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0700342585304359,"score_gpt":0.3122970242541789,"score_spread":0.242262765723743,"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."}}