{"id":"W6936374430","doi":"10.58052/ieagr003o","title":"2017-08-24-Yukon-kit-33-archive Grab Liquid>aqueous river water","year":2017,"lang":"en","type":"other","venue":"System for Earth Sample Registration (SESAR)","topic":"Mathematics and Applications","field":"Mathematics","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0006083846,0.0006615742,0.001013867,0.0002409292,0.000537849,0.0002745976,0.0007529314,0.000530194,0.0006104358],"category_scores_gemma":[0.0003019554,0.0005223571,0.0004613955,0.00006128699,0.000224667,0.0001020742,0.0001016027,0.0002659532,0.0006665859],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006791853,"about_ca_system_score_gemma":0.0001715735,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006142583,"about_ca_topic_score_gemma":0.002058752,"domain_scores_codex":[0.9970285,0.0001032727,0.0008713026,0.000788677,0.000562289,0.0006460156],"domain_scores_gemma":[0.9954505,0.0004500376,0.001390091,0.002287657,0.0002071813,0.0002145317],"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":[0.00003354472,0.0001263879,0.000001584656,0.004101474,0.0002296492,0.000007911865,0.0004363816,0.000001837873,0.0002061701,0.102418,0.8920796,0.00035748],"study_design_scores_gemma":[0.0006718314,0.0001630021,0.000001350951,0.001228419,0.0002342746,0.00005819011,0.0001155547,0.0003132716,0.000627239,0.01934241,0.9765896,0.0006549222],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.0001453635,0.0003548043,0.3961544,0.0004722749,0.001263855,0.007549451,0.008496942,0.001121482,0.5844414],"genre_scores_gemma":[0.004652904,0.0001115349,0.09036202,0.00003688475,0.001798502,0.001585709,0.002665552,0.0008759874,0.8979109],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.3134695,"threshold_uncertainty_score":0.9997228,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07370738561167094,"score_gpt":0.3205417859939321,"score_spread":0.2468344003822612,"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."}}