{"id":"W4393536876","doi":"10.5281/zenodo.7969574","title":"FABLE Scenathon database 2019","year":2023,"lang":"en","type":"dataset","venue":"IIASA PURE (International Institute of Applied Systems Analysis)","topic":"Bioeconomy and Sustainability Development","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science","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":[0.001234893,0.001426194,0.0009671006,0.004669932,0.0004678437,0.003271845,0.002218142,0.001358383,0.1194906],"category_scores_gemma":[0.007259911,0.0004949523,0.001015813,0.007260334,0.0001936204,0.002427049,0.001481747,0.0008976335,0.05972927],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002356823,"about_ca_system_score_gemma":0.002312116,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04670664,"about_ca_topic_score_gemma":0.0440296,"domain_scores_codex":[0.9992419,0.0001238285,0.0001124625,0.0001538046,0.0002830357,0.00008496743],"domain_scores_gemma":[0.9976159,0.0007429516,0.0002202237,0.0003660273,0.0009125484,0.0001424041],"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":[0.0001712133,0.00002778683,0.002310019,0.001021854,0.00006116372,0.00009759078,0.00005171054,0.004498088,0.0002206749,0.003919044,0.9659089,0.02171188],"study_design_scores_gemma":[0.0001192011,0.00002227718,0.002814313,0.0003412295,0.00003153791,0.00005737779,0.00007890951,0.003337426,0.0003595903,0.005269967,0.9875222,0.00004608527],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0006515482,0.0004073518,0.001478694,0.0002979297,0.00005333676,0.00004788495,0.9826744,0.00446603,0.009922708],"genre_scores_gemma":[0.004390847,0.0004477981,0.002576849,0.0002040722,0.00001848659,0.0001219847,0.9878439,0.0008311115,0.003564991],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1194906,"threshold_uncertainty_score":0.3997357,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01687717044776272,"score_gpt":0.2382223260514025,"score_spread":0.2213451556036398,"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."}}