{"id":"W4213336089","doi":"10.3390/rs14040928","title":"Can GPM IMERG Capture Extreme Precipitation in North China Plain?","year":2022,"lang":"en","type":"article","venue":"Remote Sensing","topic":"Precipitation Measurement and Analysis","field":"Earth and Planetary Sciences","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Global Precipitation Measurement; Environmental science; Precipitation; Climatology; Meteorology; Satellite; Geology; Geography","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":[0.0004726478,0.0006732496,0.0003952525,0.0009261589,0.0002112687,0.0008367554,0.000615647,0.0005201497,0.0009014029],"category_scores_gemma":[0.001030619,0.0001881051,0.000371524,0.001327333,0.0001692677,0.001046811,0.0004305996,0.0004013006,0.0003373721],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002841796,"about_ca_system_score_gemma":0.0004948768,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02603509,"about_ca_topic_score_gemma":0.03445164,"domain_scores_codex":[0.9998454,0.00002414858,0.000009602857,0.00005330016,0.0000326696,0.00003478762],"domain_scores_gemma":[0.9998327,0.00002295051,0.00002892431,0.00003465057,0.00006040614,0.00002024827],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005588147,0.0003460588,0.5278869,0.0002663666,0.0004020007,0.0006584005,0.0004343796,0.1854152,0.01482948,0.001319804,0.01564487,0.2522379],"study_design_scores_gemma":[0.00007339421,0.00004788554,0.2922077,0.0000295949,0.00007578569,0.00008214229,0.0002305382,0.7000856,0.002340038,0.0006859749,0.004099743,0.00004160677],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9738804,0.0004842661,0.01543384,0.0004671808,0.0001090632,0.00006989281,0.004769513,0.001411822,0.003374145],"genre_scores_gemma":[0.9772456,0.0002597036,0.01479567,0.0001046975,0.00006850855,0.00004125411,0.006621758,0.00008620427,0.000776588],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02603509,"threshold_uncertainty_score":0.05176711,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0239873336783546,"score_gpt":0.2088155545295356,"score_spread":0.184828220851181,"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."}}