{"id":"W6948881912","doi":"10.5203/ev5q-9n66","title":"Souris River Flood Extent 2011 - Part 2 Shapefiles","year":2019,"lang":"en","type":"dataset","venue":"UMANCEOS","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Manitoba","funders":"","keywords":"Flood myth; Hydrology (agriculture); Shapefile; Flooding (psychology)","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","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0003425232,0.0009164124,0.001016629,0.0003808589,0.0001666168,0.0001150081,0.001527716,0.0006680285,0.03964253],"category_scores_gemma":[0.00006941399,0.0008785904,0.0003862244,0.0001671916,0.0002868088,0.0002703351,0.0005821057,0.0009852514,0.6273827],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000253839,"about_ca_system_score_gemma":0.0001996499,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008050535,"about_ca_topic_score_gemma":0.0003399456,"domain_scores_codex":[0.995779,0.0001545947,0.0006538117,0.001314554,0.001086922,0.001011093],"domain_scores_gemma":[0.9959591,0.00008965049,0.0006682092,0.002883378,0.0001555144,0.0002441737],"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":[0.00005793401,0.0002824109,0.00005536298,0.0002597564,0.0002446027,0.0000895154,0.00005090184,0.00002604943,0.00001341179,0.000005701836,0.9986274,0.0002870087],"study_design_scores_gemma":[0.0008596076,0.0001088959,0.0008225973,0.0003433836,0.0003842052,0.00002055436,0.00001775923,0.00002603506,0.0000291112,0.00007052859,0.9962504,0.001066958],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0003769845,0.002310809,0.000002199444,0.00002631273,0.002439929,0.0009562929,0.9932705,0.0002038556,0.0004131181],"genre_scores_gemma":[0.0000192145,0.0009222378,0.0001228171,0.0002811564,0.002035856,0.0002286203,0.9908048,0.0002495582,0.005335756],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.5877402,"threshold_uncertainty_score":0.9993665,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03511602869621819,"score_gpt":0.2676943567464047,"score_spread":0.2325783280501865,"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."}}