{"id":"W6931787686","doi":"10.5683/sp/zpm1ha","title":"SLAP field data sampling: Manitoba [Canada] October 30 to November 12, 2015 dataset","year":2017,"lang":"en","type":"dataset","venue":"Borealis","topic":"Meta-analysis and systematic reviews","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Water content; Data set; Moisture; Soil water; Temperature measurement; Hydrology (agriculture)","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002536877,0.001612703,0.00193167,0.00575314,0.001650432,0.002689222,0.003686003,0.001478032,0.05808911],"category_scores_gemma":[0.02229101,0.0009563809,0.001630337,0.01650246,0.000604313,0.0006189682,0.001680015,0.001558575,0.01884408],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01204035,"about_ca_system_score_gemma":0.05008027,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8134152,"about_ca_topic_score_gemma":0.9021417,"domain_scores_codex":[0.9979141,0.0003317655,0.0005107786,0.0003881881,0.0005663746,0.0002886651],"domain_scores_gemma":[0.9840709,0.002451934,0.001655247,0.001522235,0.009378632,0.0009210323],"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":[0.0001256386,0.0000165422,0.002211575,0.002315871,0.0001575324,0.00002722701,0.00004131662,0.0003438902,0.00006143044,0.0004395118,0.9922351,0.002024384],"study_design_scores_gemma":[0.001189221,0.00002821107,0.02688766,0.003052333,0.0003019982,0.00005257229,0.000206342,0.0004923769,0.0002571693,0.001017655,0.9664363,0.00007815578],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00008209757,0.00007931447,0.00003398356,0.00004298137,0.000008336262,0.00005081062,0.9994005,0.00004287976,0.0002591691],"genre_scores_gemma":[0.00123506,0.0002178376,0.0005844081,0.0001162695,0.000008262282,0.0008113424,0.9958317,0.00004517224,0.001150005],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1865848,"threshold_uncertainty_score":0.3753673,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.7790641998849394,"score_gpt":0.5480625206940625,"score_spread":0.2310016791908769,"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."}}