{"id":"W3122928179","doi":"10.20944/preprints201701.0128.v1","title":"The Precipitation Variations in the Qinghai-Xizang (Tibetan) Plateau during 1961-2015","year":2017,"lang":"en","type":"preprint","venue":"Preprints.org","topic":"Environmental Changes in China","field":"Environmental Science","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"Science North","funders":"National Natural Science Foundation of China","keywords":"Precipitation; Plateau (mathematics); Environmental science; Climatology; Spatial distribution; Water cycle; Altitude (triangle); Spatial variability; Atmospheric sciences; Physical geography; Geography; Geology; Meteorology","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":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.002277388,0.0004229767,0.0002800443,0.00005986132,0.001098562,0.0002243556,0.003007613,0.0003284819,0.001059337],"category_scores_gemma":[0.0005935755,0.0003059648,0.0001684687,0.0001184081,0.0004867978,0.000462895,0.005398311,0.001477783,0.003467581],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009909535,"about_ca_system_score_gemma":0.0000270595,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00120053,"about_ca_topic_score_gemma":0.001544841,"domain_scores_codex":[0.9964795,0.0004387645,0.0005588432,0.001044494,0.0009092414,0.0005691989],"domain_scores_gemma":[0.9960782,0.0003615457,0.0005915898,0.002862798,0.000009719054,0.00009612986],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0000339498,0.0001559128,0.9781353,0.00004214548,0.00004863927,0.00001674156,0.01024527,0.007387653,0.002624888,0.0002582018,0.0001468562,0.000904362],"study_design_scores_gemma":[0.000272924,0.00001036761,0.98329,0.00009528173,0.00004002525,0.00001144088,0.0003487021,0.0005177566,0.002594146,0.008944291,0.003518679,0.0003563451],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.951827,0.0001390675,0.00006582618,0.003231147,0.0008676816,0.00139151,0.00002215814,0.00007427696,0.04238137],"genre_scores_gemma":[0.9955425,0.0004530429,0.0001951034,0.000112583,0.0002025554,0.0006017705,0.00004259621,0.00005172169,0.002798183],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04371548,"threshold_uncertainty_score":0.9999393,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08641661573176165,"score_gpt":0.3406999992468353,"score_spread":0.2542833835150736,"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."}}