{"id":"W4394213544","doi":"10.6084/m9.figshare.1560040","title":"Observing Bird Populations using a Distance Based Dataset","year":2015,"lang":"en","type":"dataset","venue":"Figshare","topic":"Wildlife Ecology and Conservation","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Geography; Distance sampling; Statistics; Cartography; Biology; Mathematics; Ecology; Habitat","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":[0.000470088,0.0009413308,0.0007675699,0.002043582,0.0006722859,0.0009072886,0.001346303,0.001029287,0.004592919],"category_scores_gemma":[0.0019313,0.0002935919,0.0007936913,0.003090735,0.0002629042,0.000698976,0.0009818793,0.0007898679,0.006540681],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001818051,"about_ca_system_score_gemma":0.001504607,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1539413,"about_ca_topic_score_gemma":0.4055818,"domain_scores_codex":[0.9990243,0.0001016791,0.00007353188,0.0003976125,0.0002739283,0.0001290077],"domain_scores_gemma":[0.9982485,0.0001657672,0.0001725285,0.0003776375,0.0007363398,0.0002992363],"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":[0.0008039107,0.0005919338,0.2462596,0.001827311,0.0004864383,0.0004674623,0.0008344398,0.007616545,0.008038179,0.001137799,0.6539524,0.07798397],"study_design_scores_gemma":[0.0001400648,0.0002671343,0.6624657,0.0002523028,0.0001084768,0.0003562348,0.001083334,0.02065735,0.003351607,0.0005920014,0.310607,0.0001188223],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.05778855,0.0004795442,0.002115842,0.0001810814,0.0001061444,0.0001748821,0.9343515,0.001397958,0.003404522],"genre_scores_gemma":[0.03604388,0.0001163673,0.005119254,0.00004138866,0.00002188749,0.0001588626,0.9567326,0.00005494937,0.001710809],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1539413,"threshold_uncertainty_score":0.3060905,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1623169499593539,"score_gpt":0.3151111756907403,"score_spread":0.1527942257313864,"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."}}