{"id":"W4295315060","doi":"10.5281/zenodo.7051084","title":"Deliverable 2.12 Observational gaps revealed by model sensitivity to observations","year":2018,"lang":"en","type":"report","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Meteorological Phenomena and Simulations","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Horizon 2020 Framework Programme","keywords":"Deliverable; Sensitivity (control systems); Observational study; Environmental science; Medicine; Internal medicine; Engineering; Systems engineering","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":[0.003497374,0.001798495,0.001329131,0.001443102,0.0006094147,0.003400065,0.003731713,0.002349324,0.2695307],"category_scores_gemma":[0.01528165,0.0008371231,0.002252823,0.001984263,0.0003303687,0.002796708,0.002503186,0.001682733,0.1319539],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001233206,"about_ca_system_score_gemma":0.002344463,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02121585,"about_ca_topic_score_gemma":0.01117386,"domain_scores_codex":[0.9988024,0.0002258264,0.00006906753,0.0002423085,0.0005064861,0.000153871],"domain_scores_gemma":[0.995819,0.001582197,0.0001828017,0.001033893,0.001163164,0.0002189282],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004306299,0.00007789536,0.001933263,0.0006015612,0.0001769557,0.0002083982,0.00008051224,0.07114608,0.001258492,0.007728899,0.8815194,0.03483782],"study_design_scores_gemma":[0.0007349984,0.0001760445,0.003550387,0.0004487645,0.0001165801,0.0002000204,0.000205295,0.2871127,0.005646917,0.05315259,0.6484246,0.0002311536],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.004230875,0.000283632,0.09943924,0.002169591,0.001519197,0.0004673866,0.7712723,0.07659448,0.04402326],"genre_scores_gemma":[0.0417929,0.000597331,0.07170905,0.0007520707,0.0004997231,0.001794674,0.8023688,0.0306058,0.04987969],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.2695307,"threshold_uncertainty_score":0.90167,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1811806428425146,"score_gpt":0.2790183727481034,"score_spread":0.09783772990558881,"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."}}