{"id":"W6910385135","doi":"10.48511/cs9v-9d70","title":"Gray Creek Hydrometric","year":2023,"lang":"en","type":"dataset","venue":"Columbia Basin Water Hub","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Structural basin; Shore; Gray (unit); Hydrology (agriculture); Climate change; Water resources; Water supply","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":[0.0007666869,0.001165592,0.0009661429,0.00247229,0.0008232787,0.001582913,0.002279337,0.001070633,0.05077872],"category_scores_gemma":[0.004176403,0.0004509778,0.0006497902,0.006112086,0.0003186156,0.001300171,0.001408952,0.001401212,0.0634164],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002118821,"about_ca_system_score_gemma":0.003048657,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1377078,"about_ca_topic_score_gemma":0.2377401,"domain_scores_codex":[0.9991238,0.0001230892,0.00008032242,0.0002344232,0.000310211,0.000128234],"domain_scores_gemma":[0.9981773,0.0002211016,0.0001131305,0.0003446245,0.0009819738,0.0001619548],"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":[0.000024463,0.00001087283,0.001086415,0.000147417,0.00001086538,0.00001161245,0.00001556185,0.0002203732,0.0000371949,0.0004186127,0.9957397,0.002276885],"study_design_scores_gemma":[0.00007029781,0.000005724541,0.005596294,0.000132945,0.000009098987,0.00002488363,0.0000776102,0.0007126773,0.0001679949,0.001162977,0.9920156,0.00002393979],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001552996,0.00002934801,0.00006226932,0.00005093691,0.00001275712,0.000006896007,0.9984633,0.0002634536,0.0009557902],"genre_scores_gemma":[0.0004697023,0.00002677354,0.0002729698,0.00002937448,0.000003955105,0.00003664356,0.9984207,0.00006619251,0.0006736717],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1377078,"threshold_uncertainty_score":0.2738125,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02261822251166183,"score_gpt":0.2517347255663781,"score_spread":0.2291165030547163,"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."}}