{"id":"W2390515989","doi":"","title":"A water supply function in form of Weibull distribution","year":2003,"lang":"en","type":"article","venue":"Xibei zhiwu xuebao","topic":"Water Resources and Sustainability","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Science North","funders":"","keywords":"Weibull distribution; Kurtosis; Water supply; Range (aeronautics); Function (biology); Skew; Mathematics; Shape parameter; Statistics; Environmental science; Computer science; Environmental engineering; Engineering","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0003475296,0.00009099424,0.0001169683,0.00001886768,0.00004846152,0.00001230343,0.00008599791,0.00005968142,0.002188653],"category_scores_gemma":[0.00002618843,0.00006354893,0.00005021588,0.000130989,0.00008716819,0.0001579805,0.00005910249,0.00008058999,0.0001510154],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002213994,"about_ca_system_score_gemma":0.00000470496,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008945758,"about_ca_topic_score_gemma":0.0002614802,"domain_scores_codex":[0.9990606,0.0000544808,0.0002081262,0.0002051773,0.0001754809,0.0002961639],"domain_scores_gemma":[0.9996992,0.00001044643,0.00002868473,0.0002028311,0.000007515277,0.00005127071],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001256806,0.0003166268,0.9804715,0.00004700218,0.00000753192,0.000009367946,0.002203351,0.0005970459,0.007720164,0.00102708,0.002376107,0.005098535],"study_design_scores_gemma":[0.0007961232,0.000218059,0.4423915,0.00001005798,0.0000134954,0.000006345513,0.0004865234,0.0002945994,0.0502074,0.01950944,0.4858328,0.0002337439],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.991881,0.00001175956,0.0005346833,0.0001733787,0.00005495353,0.0001854049,0.000007753095,0.00001457504,0.007136488],"genre_scores_gemma":[0.9982817,0.00000201467,0.00005475232,0.00002853901,0.000007764531,0.00001570628,0.00003080533,0.000005984344,0.001572775],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.53808,"threshold_uncertainty_score":0.9987235,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004113042377529453,"score_gpt":0.1820097172033475,"score_spread":0.177896674825818,"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."}}