{"id":"W2952449087","doi":"","title":"The Canadian Hydrometeorological Information and Prediction System (CHIPS)","year":2001,"lang":"en","type":"article","venue":"The 81st AMS Annual Meeting","topic":"Hydrology and Watershed Management Studies","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Hydrometeorology; Computer science; Environmental science; Meteorology; Precipitation; Geography","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":[0.001686049,0.00134545,0.0009889591,0.006419292,0.003061338,0.002935344,0.002096622,0.0007687191,0.01990571],"category_scores_gemma":[0.008692463,0.0006644932,0.0006274816,0.01187398,0.0006422159,0.001647372,0.001376823,0.00102167,0.008825734],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02812942,"about_ca_system_score_gemma":0.09611661,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9937385,"about_ca_topic_score_gemma":0.9943641,"domain_scores_codex":[0.9985201,0.00007187296,0.00007426798,0.000169063,0.000925153,0.000239575],"domain_scores_gemma":[0.9893146,0.000392101,0.000411341,0.0007582067,0.008145728,0.0009781116],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001262391,0.00005384717,0.02681257,0.0001574851,0.00009626396,0.0000472848,0.0001388191,0.007456161,0.00113535,0.005231198,0.8197665,0.1389782],"study_design_scores_gemma":[0.0001579353,0.00002921462,0.09451073,0.000207433,0.000180128,0.00005358096,0.000305829,0.07659999,0.003609349,0.005351652,0.8187447,0.00024955],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.02362364,0.001137448,0.02385839,0.003915686,0.0005632621,0.0007387109,0.8564312,0.01886268,0.07086895],"genre_scores_gemma":[0.1310626,0.002956507,0.0720231,0.001316227,0.0002038272,0.0008770258,0.7294773,0.002158849,0.05992456],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.02812942,"threshold_uncertainty_score":0.2040942,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006169468801064678,"score_gpt":0.1813265945062491,"score_spread":0.1751571257051844,"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."}}