{"id":"W4246324606","doi":"10.5203/lwbin.cwww.2004.1","title":"2001-2004 City of Winnipeg Rivers and Streams Data","year":2015,"lang":"en","type":"dataset","venue":"","topic":"Fish Ecology and Management Studies","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"STREAMS; Geography; Environmental science; Hydrology (agriculture); Geology; Computer science; Computer network; Geotechnical engineering","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":[0.001093932,0.001879765,0.001642648,0.005983574,0.0009378935,0.00179492,0.00260172,0.001143935,0.01584147],"category_scores_gemma":[0.006105207,0.001272938,0.001158304,0.01483712,0.0003439909,0.000588027,0.001522099,0.001025847,0.01171196],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00459855,"about_ca_system_score_gemma":0.01331528,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.7558499,"about_ca_topic_score_gemma":0.7971449,"domain_scores_codex":[0.9988173,0.00009722362,0.0001650672,0.000269459,0.000370976,0.0002800106],"domain_scores_gemma":[0.9970936,0.0002608978,0.0005328165,0.0003568096,0.001358686,0.0003971839],"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":[0.0001895806,0.00003231191,0.01553631,0.000732142,0.0001979418,0.00007985849,0.00008563325,0.001020116,0.0001265173,0.0005097092,0.9776661,0.003823754],"study_design_scores_gemma":[0.0003134883,0.00001803653,0.1366214,0.0004658394,0.0001735518,0.00008700549,0.0001973322,0.0007838594,0.0004215398,0.0004069398,0.8604658,0.00004508335],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0006362859,0.0000589101,0.00003355239,0.00002418062,0.0000101513,0.00001478922,0.9988775,0.00004161336,0.0003030595],"genre_scores_gemma":[0.001949806,0.00008920598,0.0001878749,0.00002849145,0.000004339101,0.00008902547,0.9962122,0.00003290479,0.001406049],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.2441501,"threshold_uncertainty_score":0.4911759,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03833764170039189,"score_gpt":0.2634032550029798,"score_spread":0.225065613302588,"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."}}