{"id":"W1993383230","doi":"10.1016/j.biocon.2014.02.010","title":"Maps, models, and marine vulnerability: Assessing the community distribution of seabirds at-sea","year":2014,"lang":"en","type":"article","venue":"Biological Conservation","topic":"Avian ecology and behavior","field":"Environmental Science","cited_by":27,"is_retracted":false,"has_abstract":false,"ca_institutions":"Environment and Climate Change Canada; Mount Allison University","funders":"Environmental Studies Research Funds; Mount Allison University","keywords":"Bathymetry; Environmental science; Seabird; Species distribution; Sampling (signal processing); Vulnerability (computing); Geography; Submarine pipeline; Aerial survey; Physical geography; Habitat; Fishery; Ecology; Oceanography; Cartography; Computer science; Biology; Predation","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001765363,0.0006658369,0.0003175276,0.002810383,0.0003166787,0.001659568,0.0006317388,0.0006789762,0.001658236],"category_scores_gemma":[0.009689337,0.0002776471,0.0005279809,0.001879694,0.0005522965,0.001547807,0.0009319226,0.0003078546,0.0001688397],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008206954,"about_ca_system_score_gemma":0.0005669416,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02617263,"about_ca_topic_score_gemma":0.02965971,"domain_scores_codex":[0.9994159,0.0003636242,0.00001906625,0.00006141212,0.00009409473,0.00004592384],"domain_scores_gemma":[0.9955871,0.00333902,0.0004570502,0.0001967282,0.000264844,0.0001551237],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0002837771,0.0001571529,0.2010961,0.00008276766,0.0004111077,0.00009992409,0.0002473711,0.7552313,0.0003316065,0.003680552,0.001293792,0.03708461],"study_design_scores_gemma":[0.00002868617,0.0001013221,0.04574378,0.0000291133,0.0001115206,0.0001069764,0.0004673089,0.9411864,0.0002539008,0.01131075,0.0006374834,0.00002272901],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.981309,0.0003830671,0.01524358,0.0003172138,0.00001716845,0.00001892019,0.0007181398,0.0001837168,0.001809287],"genre_scores_gemma":[0.9943441,0.0001344717,0.004828861,0.000009714837,0.000008875794,0.00001176911,0.0003096381,0.00001408081,0.0003385921],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02617263,"threshold_uncertainty_score":0.05204058,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07307902107966942,"score_gpt":0.2876948535988534,"score_spread":0.214615832519184,"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."}}