{"id":"W7139953882","doi":"10.21966/chc3-rj93","title":"Biogeochemical Sampling of 28 Streams on Vancouver Island","year":2018,"lang":"","type":"dataset","venue":"Hakai Institute","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"STREAMS; Sampling (signal processing); Dissolved organic carbon; Biogeochemical cycle; Hydrology (agriculture); Water quality; Biogeochemistry","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":[],"consensus_categories":[],"category_scores_codex":[0.0003977345,0.0006204217,0.0005887342,0.002210298,0.001014803,0.001410825,0.0008599841,0.0004527472,0.007722837],"category_scores_gemma":[0.001599847,0.0003312647,0.000276852,0.005646241,0.0002445637,0.000243515,0.0007859778,0.0007427941,0.0048158],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002884768,"about_ca_system_score_gemma":0.005811983,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.6915751,"about_ca_topic_score_gemma":0.8443397,"domain_scores_codex":[0.9994886,0.00003686463,0.00003555543,0.0001382026,0.0002036927,0.00009706109],"domain_scores_gemma":[0.9988118,0.00008048095,0.00008476069,0.0001226667,0.0007389071,0.0001612968],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.0003085414,0.0001610168,0.1805006,0.0009404093,0.0002037928,0.000437108,0.0007226549,0.002603376,0.001472479,0.00104418,0.7556531,0.05595279],"study_design_scores_gemma":[0.00009970985,0.00002055999,0.2725525,0.0004822476,0.00006003082,0.0001058325,0.0009345619,0.00216775,0.001168145,0.0005253906,0.7218224,0.0000607855],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.02579511,0.0002750973,0.0003280937,0.00009846519,0.00003410666,0.00008403808,0.9667948,0.0002894224,0.006300777],"genre_scores_gemma":[0.0302905,0.0002718803,0.001356206,0.00005497596,0.00001255087,0.0002175858,0.962559,0.00008196756,0.005155389],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.3084249,"threshold_uncertainty_score":0.6204825,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03562589417271188,"score_gpt":0.2962231769528923,"score_spread":0.2605972827801804,"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."}}