{"id":"W7133337699","doi":"10.58052/ieagr00l7","title":"2013-05-15-Yukon-kit-5-archive Grab Liquid>aqueous river water","year":2013,"lang":"","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":[],"category_scores_codex":[0.001688724,0.001536534,0.001098121,0.004199625,0.001546716,0.002688988,0.00232024,0.001470431,0.2944009],"category_scores_gemma":[0.003313139,0.001353243,0.0009173625,0.00299975,0.0006417304,0.002178902,0.002748836,0.0008350083,0.3126979],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001885437,"about_ca_system_score_gemma":0.00496771,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04631846,"about_ca_topic_score_gemma":0.09221975,"domain_scores_codex":[0.9986696,0.0001247855,0.0001499541,0.0003138369,0.0005270587,0.0002147399],"domain_scores_gemma":[0.9979127,0.0002629766,0.0001765151,0.0005353499,0.000971336,0.0001411454],"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":[0.0007084719,0.0001325816,0.005816942,0.0009696221,0.00007456273,0.0001205927,0.0002180266,0.0007236689,0.01299277,0.003375044,0.8769667,0.09790101],"study_design_scores_gemma":[0.0001508023,0.00004362717,0.006326594,0.00009269563,0.00003530571,0.0000748716,0.0001313569,0.001388478,0.01737849,0.001588325,0.9727029,0.00008661303],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.007532323,0.0003523721,0.03159839,0.0005100422,0.0002496761,0.001096112,0.7570276,0.08089216,0.1207413],"genre_scores_gemma":[0.02252089,0.0004765785,0.0625438,0.0006796836,0.00007814553,0.002069545,0.7285981,0.03551333,0.1475199],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.7055991,"threshold_uncertainty_score":0.984869,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02155902329111766,"score_gpt":0.2447701531216331,"score_spread":0.2232111298305154,"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."}}