{"id":"W6892217732","doi":"10.5066/p9pndsxr","title":"Code associated with analysis and modeling of benthic and pelagic inorganic nutrient processing rates at the interface between a river and lake","year":2021,"lang":"en","type":"dataset","venue":"USGS DOI Tool Production Environment","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Trent University","funders":"","keywords":"Sediment–water interface; Benthic zone; Water column; Nutrient; Hydrology (agriculture); Code (set theory); Interface (matter); Nitrate","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001078321,0.00058566,0.0009075802,0.0003391594,0.0004319114,0.0001394438,0.0001777882,0.0002726073,0.0001882359],"category_scores_gemma":[0.0001905321,0.0004415424,0.00007468432,0.0006894653,0.0008170847,0.0002629972,0.0006606819,0.0006328142,0.00001932732],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004384916,"about_ca_system_score_gemma":0.00005764902,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007222258,"about_ca_topic_score_gemma":0.0008671888,"domain_scores_codex":[0.9963271,0.0003996162,0.0006762377,0.001431019,0.0007970275,0.0003690012],"domain_scores_gemma":[0.9980181,0.00008720871,0.0009083404,0.0007955348,0.00008146777,0.00010928],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.002070226,0.004510309,0.3136534,0.005757447,0.04499319,0.00008275432,0.02142091,0.282765,0.01479858,0.000003613578,0.3036363,0.006308217],"study_design_scores_gemma":[0.01075508,0.002099211,0.3320883,0.005213759,0.1237103,0.0003901463,0.008180512,0.04860717,0.03083404,0.0002632389,0.4288125,0.009045777],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"dataset","genre_scores_codex":[0.5521064,0.005430451,0.0002094813,0.0002148651,0.00002739411,0.0006492779,0.4413399,0.00002162488,6.501759e-7],"genre_scores_gemma":[0.4495665,0.003278082,0.0001356764,0.00001555866,0.0001052053,0.00006259766,0.5465724,0.00008877528,0.0001752311],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.2341578,"threshold_uncertainty_score":0.9998037,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0174938909601379,"score_gpt":0.2446227092993603,"score_spread":0.2271288183392224,"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."}}