{"id":"W4399577333","doi":"10.32614/cran.package.detect","title":"detect: Analyzing Wildlife Data with Detection Error","year":2011,"lang":"en","type":"dataset","venue":"","topic":"Identification and Quantification in Food","field":"Biochemistry, Genetics and Molecular Biology","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Wildlife; Computer science; Geography; Biology; Ecology","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":[0.02319209,0.002635553,0.002432954,0.004177561,0.000946144,0.004031247,0.005993411,0.002856558,0.01304132],"category_scores_gemma":[0.08882992,0.002289384,0.005405867,0.004170276,0.0014903,0.005870518,0.004598554,0.005419816,0.005911688],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00221001,"about_ca_system_score_gemma":0.003572384,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01617168,"about_ca_topic_score_gemma":0.01571384,"domain_scores_codex":[0.9889755,0.00576856,0.0007090495,0.00242599,0.001852617,0.0002683432],"domain_scores_gemma":[0.9379045,0.04724345,0.003393164,0.008464443,0.002313703,0.0006807654],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001113913,0.0007520724,0.05861339,0.002019198,0.004214788,0.000579469,0.0006658326,0.3897976,0.002419187,0.05385724,0.1160147,0.3699526],"study_design_scores_gemma":[0.0001666466,0.0001472898,0.004852074,0.0001578441,0.000209829,0.0002110574,0.00006946765,0.9226882,0.001040549,0.05436313,0.01599026,0.0001035887],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"dataset","genre_scores_codex":[0.009446307,0.0008470102,0.9609915,0.001280188,0.0003579882,0.0003439562,0.009405486,0.01601354,0.001314016],"genre_scores_gemma":[0.137307,0.001109944,0.8217699,0.001445289,0.0006165031,0.002043122,0.02251117,0.006097534,0.007099688],"genre_candidate":"dataset","genre_consensus":null,"teacher_disagreement_score":0.02319209,"threshold_uncertainty_score":0.1226529,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05339149696102556,"score_gpt":0.2991228085906537,"score_spread":0.2457313116296281,"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."}}