{"id":"W4393597569","doi":"10.5281/zenodo.4923989","title":"Karnali River Suspended Sediment Sampling","year":2021,"lang":"en","type":"dataset","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Groundwater and Watershed Analysis","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"Research Councils UK","keywords":"Sampling (signal processing); Sediment; Hydrology (agriculture); Environmental science; Geology; Geomorphology; Computer science; Geotechnical engineering; Telecommunications","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","sts","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0005603883,0.0002581051,0.0002633858,0.0001531518,0.001734565,0.0009195704,0.001387844,0.0001349914,0.2072599],"category_scores_gemma":[0.0001346143,0.0002539491,0.0001234248,0.0005247379,0.0002545868,0.0002103672,0.003314458,0.0004426845,0.04693339],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004549176,"about_ca_system_score_gemma":0.000002100699,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004299794,"about_ca_topic_score_gemma":0.00000426747,"domain_scores_codex":[0.9973991,0.000356768,0.0003138252,0.0007209912,0.0007246862,0.0004846441],"domain_scores_gemma":[0.9987348,0.00001533995,0.0001373776,0.0007915153,0.00008938558,0.0002315904],"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":[0.0000120826,0.0001082678,0.00000286508,0.00003541889,0.00008298364,0.00004872236,0.000196006,0.0001438146,0.0004319443,0.00001044606,0.9935803,0.005347078],"study_design_scores_gemma":[0.0002321271,0.00006199721,0.0001252277,0.00002818973,0.00008600637,0.00006446155,0.0000922785,0.00002763168,0.0001484049,0.000101122,0.9987427,0.0002898577],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.001192006,0.00006627108,0.0007581721,0.0004615342,0.0002580669,0.0004053797,0.9775527,0.000357847,0.018948],"genre_scores_gemma":[0.002445139,0.0001447444,0.0001976229,0.0002150514,0.0001542117,3.659272e-8,0.994811,0.000662951,0.001369237],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1603265,"threshold_uncertainty_score":0.9999913,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03513113849726093,"score_gpt":0.2458347310126049,"score_spread":0.210703592515344,"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."}}