{"id":"W6964386735","doi":"10.25976/h1bf-4i49","title":"RivTemp--National_Defence","year":2021,"lang":"en","type":"dataset","venue":"DataStream","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"General partnership; Variety (cybernetics); Foundation (evidence); Watershed; Oncorhynchus","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":[0.001081913,0.001633934,0.001187131,0.003625273,0.00105539,0.002758516,0.002667336,0.001454526,0.1183779],"category_scores_gemma":[0.005969203,0.0009761503,0.001047284,0.01028218,0.0003581526,0.001894398,0.002067964,0.002077651,0.1665073],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002793708,"about_ca_system_score_gemma":0.005594491,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1496379,"about_ca_topic_score_gemma":0.2002325,"domain_scores_codex":[0.9986651,0.0001514889,0.0001367497,0.0003634263,0.000404834,0.0002782728],"domain_scores_gemma":[0.997015,0.0005134498,0.0002676014,0.0006921919,0.001222165,0.0002895487],"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":[0.00002104546,0.000006601346,0.0004850419,0.0001535472,0.000008744219,0.000006214225,0.00001442242,0.00009769215,0.00003554273,0.0003176556,0.9978061,0.001047448],"study_design_scores_gemma":[0.00007656949,0.000006091895,0.003241005,0.0001813376,0.000009883211,0.00001957324,0.0000770551,0.0002183287,0.0001662769,0.0005283207,0.9954569,0.00001859069],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004449411,0.00001098037,0.00002174728,0.00002622323,0.000008271557,0.00000392012,0.9991511,0.000100902,0.0006322979],"genre_scores_gemma":[0.0001338136,0.00001617303,0.0001033083,0.00001548649,0.000001888412,0.00003266372,0.9989316,0.00005875899,0.0007062166],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1496379,"threshold_uncertainty_score":0.3960137,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02274580694292508,"score_gpt":0.2938181211232099,"score_spread":0.2710723141802848,"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."}}