{"id":"W6899019521","doi":"10.58052/ieagr00bb","title":"2024-08-24-Yukon-kit-69-archive Grab Liquid>aqueous river water","year":2024,"lang":"en","type":"other","venue":"System for Earth Sample Registration (SESAR)","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Hydrology (agriculture); Water resources; Work (physics); Water quality; Shore","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":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0008872185,0.001276055,0.0008076687,0.002519425,0.001399377,0.00218872,0.001785007,0.001556358,0.5733311],"category_scores_gemma":[0.002122451,0.00096179,0.0006491801,0.001804043,0.0004972793,0.001514142,0.002034369,0.0007138514,0.5498443],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002054669,"about_ca_system_score_gemma":0.003764612,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0665406,"about_ca_topic_score_gemma":0.1221361,"domain_scores_codex":[0.9992975,0.00006268974,0.00005458762,0.0001501703,0.0002813331,0.0001536399],"domain_scores_gemma":[0.9987232,0.0001517175,0.0000712266,0.0002789951,0.0006502005,0.0001247084],"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":[0.0002680456,0.00008174011,0.002041105,0.0003744015,0.00002313528,0.00005781991,0.0001228685,0.0004058334,0.003878932,0.002155838,0.9370782,0.05351203],"study_design_scores_gemma":[0.00008701258,0.00002462304,0.002773207,0.00005280404,0.00001010011,0.00003753448,0.00009808376,0.0006931002,0.004880436,0.001098185,0.9902007,0.0000440981],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.005043843,0.0001930293,0.01254064,0.0004922272,0.000267902,0.0007934839,0.6178426,0.05601895,0.3068074],"genre_scores_gemma":[0.01848309,0.0002518127,0.02116425,0.0009184898,0.00005782253,0.001334693,0.5437264,0.03077857,0.3832848],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.9334594,"threshold_uncertainty_score":0.6085913,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02461745489843895,"score_gpt":0.262397737826845,"score_spread":0.2377802829284061,"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."}}