{"id":"W6955234224","doi":"10.58052/ieagr001l","title":"2021-09-01-Yukon-kit-56-archive Grab Liquid>aqueous river water","year":2021,"lang":"en","type":"other","venue":"System for Earth Sample Registration (SESAR)","topic":"Psychiatric care and mental health services","field":"Psychology","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":[0.0008041981,0.001027391,0.0006927563,0.002200881,0.001647104,0.002115578,0.001320001,0.001321838,0.5946309],"category_scores_gemma":[0.001992136,0.0007894352,0.0005730909,0.001727027,0.0004846882,0.00139615,0.001886644,0.000649775,0.5036042],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002171446,"about_ca_system_score_gemma":0.004753253,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06802469,"about_ca_topic_score_gemma":0.1305947,"domain_scores_codex":[0.9993818,0.00005549426,0.00005405293,0.0001610795,0.000220342,0.0001271435],"domain_scores_gemma":[0.9985677,0.000156512,0.00008814193,0.0002482359,0.0008002315,0.000139275],"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":[0.000481399,0.0001259376,0.006683679,0.0005778927,0.00002743553,0.0001363743,0.0001944292,0.0004907367,0.006187984,0.002640171,0.8596936,0.1227604],"study_design_scores_gemma":[0.0001072827,0.0000451642,0.007221411,0.00007627251,0.00001147213,0.00007003812,0.0001934552,0.0007988089,0.006174342,0.001153049,0.9841034,0.00004528647],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.01332005,0.0002727481,0.01203823,0.0009784305,0.0003765888,0.001564041,0.5276524,0.04301235,0.4007851],"genre_scores_gemma":[0.03579253,0.0003462724,0.0240229,0.001247908,0.0000765718,0.001660769,0.3541716,0.01606976,0.5666117],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.9319753,"threshold_uncertainty_score":0.5782098,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02667800930479677,"score_gpt":0.3156260183561692,"score_spread":0.2889480090513724,"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."}}