{"id":"W2782151287","doi":"10.1080/03610926.2017.1414254","title":"The Marshall-Olkin logistic-exponential distribution","year":2018,"lang":"en","type":"article","venue":"Communication in Statistics- Theory and Methods","topic":"Statistical Distribution Estimation and Applications","field":"Mathematics","cited_by":44,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Bathtub; Quantile function; Mathematics; Exponential function; Exponential distribution; Order statistic; Applied mathematics; Estimator; Statistics; Log-logistic distribution; Natural exponential family; Probability density function; Logistic distribution; Hazard; Exponential family; Quantile; Moment-generating function; Cumulative distribution function; Logistic regression; Mathematical analysis","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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.005174966,0.0001516568,0.0001913135,0.00003698376,0.0008680879,0.0001137256,0.0003951963,0.00008794416,0.0002228272],"category_scores_gemma":[0.01119403,0.0001217647,0.00002797713,0.0002557956,0.001316864,0.00007342382,0.0001828085,0.0002489933,0.00003837886],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007004746,"about_ca_system_score_gemma":0.00004206653,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001381543,"about_ca_topic_score_gemma":0.00004432648,"domain_scores_codex":[0.9962609,0.002559372,0.000557674,0.0002240804,0.0001491999,0.0002487175],"domain_scores_gemma":[0.9859934,0.01265326,0.0002100135,0.0007811229,0.0002679779,0.0000942342],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00006924858,0.00006336942,0.00003610699,0.00001534185,0.00001176601,3.075944e-7,0.0001953696,4.955602e-7,0.00008561936,0.9159159,0.002812671,0.08079381],"study_design_scores_gemma":[0.0003244114,0.00003317257,0.006584771,0.00003220547,0.00003818526,0.00000625236,0.0002775402,0.004557828,0.0002801915,0.9686576,0.01906456,0.0001432709],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0007217284,0.0002572906,0.9951123,0.000543755,0.0001109206,0.0003125145,0.0005397125,0.00006607087,0.002335734],"genre_scores_gemma":[0.4750669,0.0003251712,0.523332,0.0001211422,0.00005365793,0.0001916622,0.0003906914,0.00001822986,0.000500575],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.4743451,"threshold_uncertainty_score":0.9971351,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1235645162765778,"score_gpt":0.5007064724407221,"score_spread":0.3771419561641443,"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."}}