{"id":"W4403648081","doi":"10.25303/2811rjce037047","title":"Assessment of Maximum Temperature for Future Time Series over Aurangabad, Maharashtra State, India","year":2024,"lang":"en","type":"article","venue":"Research Journal of Chemistry and Environment","topic":"Solar Radiation and Photovoltaics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Series (stratigraphy); State (computer science); Time series; Mathematics; Statistics; Geography; Algorithm; Geology","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":[0.0002152248,0.0001750854,0.0001083742,0.0006077784,0.0002027815,0.0004258294,0.0002602301,0.0001566946,0.0008038051],"category_scores_gemma":[0.000545354,0.00007755142,0.0002026727,0.00134711,0.0001204949,0.000316946,0.000183909,0.0001935729,0.0001691894],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004907292,"about_ca_system_score_gemma":0.0004593766,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03415438,"about_ca_topic_score_gemma":0.03679306,"domain_scores_codex":[0.9998831,0.00002254718,0.0000122124,0.00002833863,0.00003422581,0.00001972141],"domain_scores_gemma":[0.9996986,0.00007767104,0.00006348395,0.00002820946,0.0001122417,0.00001968756],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003835731,0.0000950296,0.8446984,0.0004079133,0.000189706,0.001080237,0.0009472021,0.0628853,0.008427784,0.00147623,0.006831462,0.07257715],"study_design_scores_gemma":[0.00001244391,0.0000896104,0.9507256,0.00002848737,0.00006589352,0.0002268182,0.0007663259,0.04160271,0.002066021,0.0002467973,0.004144991,0.00002433129],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9911134,0.0001888052,0.0009679477,0.0001765866,0.00001709151,0.00001298774,0.004281614,0.0001198907,0.003121736],"genre_scores_gemma":[0.9966663,0.0001047455,0.0005572331,0.000009705075,0.000008099008,0.00001313863,0.002353742,0.000006084145,0.0002810193],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03415438,"threshold_uncertainty_score":0.06791115,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01063420756968256,"score_gpt":0.294037718592156,"score_spread":0.2834035110224735,"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."}}