{"id":"W6930273258","doi":"10.5281/zenodo.11640826","title":"FABLE Scenathon database 2023","year":2024,"lang":"en","type":"dataset","venue":"IIASA PURE (International Institute of Applied Systems Analysis)","topic":"Wheat and Barley Genetics and Pathology","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Sustainability; Commodity; Consistency (knowledge bases); Agriculture; Scope (computer science); Futures studies; China; Agricultural productivity","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":[0.001338516,0.001473317,0.001050965,0.004824916,0.0006181261,0.003593014,0.002775436,0.001446841,0.1744442],"category_scores_gemma":[0.006898949,0.0005744343,0.001137562,0.007368074,0.0002196087,0.002713889,0.001594843,0.000967383,0.08686591],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002956868,"about_ca_system_score_gemma":0.003092056,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05656436,"about_ca_topic_score_gemma":0.04741576,"domain_scores_codex":[0.999241,0.0001177039,0.00009751481,0.0001558883,0.00029742,0.00009045847],"domain_scores_gemma":[0.997808,0.000612452,0.0001692592,0.0003917824,0.0009006429,0.0001178401],"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":[0.000164075,0.00002442056,0.001355737,0.0008977586,0.00005131004,0.00008882133,0.00005066604,0.003850408,0.0002375391,0.005660762,0.9626619,0.0249565],"study_design_scores_gemma":[0.00009432311,0.00001510709,0.001500769,0.0002582858,0.0000245966,0.00005081498,0.00005683919,0.003025196,0.0003598689,0.005285253,0.989292,0.00003683481],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0006783978,0.000521039,0.00317095,0.0003081842,0.00005410154,0.00007337517,0.96869,0.00615649,0.02034733],"genre_scores_gemma":[0.00453784,0.0004699348,0.004883253,0.0002234568,0.00001710101,0.0001755523,0.9834536,0.001250127,0.004989173],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1744442,"threshold_uncertainty_score":0.5835739,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0200932437627962,"score_gpt":0.2479938415920918,"score_spread":0.2279005978292956,"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."}}