{"id":"W4283068822","doi":"10.31234/osf.io/ygkjn","title":"d'o: Sensitivity at the optimal criterion location","year":2022,"lang":"en","type":"preprint","venue":"","topic":"Probabilistic and Robust Engineering Design","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Winnipeg","funders":"","keywords":"Observer (physics); Detection theory; Base (topology); Noise (video); Variance (accounting); Measure (data warehouse); Response bias; Set (abstract data type); Range (aeronautics); Mathematics; SIGNAL (programming language); Interpretation (philosophy); Statistics; Sensitivity (control systems); Computer science; Algorithm; Pattern recognition (psychology); Artificial intelligence; Data mining; Physics; Detector","routes":{"ca_aff":true,"ca_fund":false,"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":[0.005704393,0.0009096629,0.001120636,0.001444353,0.0005838728,0.002843264,0.001534513,0.001671266,0.002820855],"category_scores_gemma":[0.04609066,0.0006181446,0.001107331,0.0007572904,0.002595742,0.00260806,0.005135994,0.001842167,0.0004158827],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001791468,"about_ca_system_score_gemma":0.001182536,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002336098,"about_ca_topic_score_gemma":0.001111892,"domain_scores_codex":[0.9956883,0.001325904,0.000353644,0.001479895,0.0008856193,0.0002666923],"domain_scores_gemma":[0.9783273,0.01558312,0.002330479,0.00202049,0.001142025,0.000596533],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00254254,0.0003120384,0.06254685,0.001363075,0.001040695,0.0006214685,0.001579738,0.2659318,0.09607102,0.1961644,0.005721507,0.3661048],"study_design_scores_gemma":[0.000316037,0.00155002,0.0585415,0.0003321256,0.000310865,0.001370601,0.0007176604,0.5263247,0.0585187,0.3427109,0.008735708,0.0005711329],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2419592,0.001321581,0.7351183,0.0009085348,0.0002604431,0.000263987,0.0005602736,0.0009128496,0.01869478],"genre_scores_gemma":[0.9146004,0.0002127272,0.08315416,0.0004529092,0.00003958582,0.0001897195,0.0002226706,0.00015651,0.0009712412],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005704393,"threshold_uncertainty_score":0.03016806,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1071306226665074,"score_gpt":0.3541852125127003,"score_spread":0.2470545898461929,"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."}}