{"id":"W6891800042","doi":"10.48511/v606-dy73","title":"Summit Lake Level","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":"Summit; Structural basin; Climate change; Water supply; Watershed; Habitat","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.001142209,0.0008119672,0.001222652,0.0004807299,0.000415551,0.001251318,0.002091748,0.0008462904,0.01043955],"category_scores_gemma":[0.000270863,0.0009503489,0.0004305411,0.0006805938,0.0003334704,0.0002473849,0.00131323,0.001285426,0.6733016],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003328682,"about_ca_system_score_gemma":0.0002346512,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.05122379,"about_ca_topic_score_gemma":0.8051913,"domain_scores_codex":[0.9940632,0.0003788325,0.0009270178,0.001588832,0.001245816,0.001796328],"domain_scores_gemma":[0.9959442,0.0001399805,0.0002637691,0.00296772,0.0002790763,0.0004052807],"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":[0.00003230695,0.0001601126,0.0002499103,0.0003252812,0.0002378716,0.0006864438,0.00002779941,0.000003424273,0.00005786835,2.821412e-7,0.9981102,0.0001085149],"study_design_scores_gemma":[0.0008376319,0.00006257374,0.00223478,0.0002627322,0.0003481267,0.00001905427,0.00001722204,0.000002259801,0.0001350849,0.0002572494,0.9944863,0.001337038],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0006893757,0.00003282011,0.000001085043,0.0001715828,0.003557859,0.0009706392,0.9933503,0.0009060426,0.0003202691],"genre_scores_gemma":[0.00002070955,0.00003815014,0.00006318009,0.0003772074,0.001081921,0.0002891169,0.9148471,0.0005846904,0.08269794],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.7539675,"threshold_uncertainty_score":0.9997855,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05465574256558318,"score_gpt":0.2684509027147102,"score_spread":0.213795160149127,"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."}}