{"id":"W6893141610","doi":"10.5281/zenodo.14205937","title":"Atomic data for SIKE","year":2024,"lang":"en","type":"dataset","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Traffic Prediction and Management Techniques","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Kinetic energy; Preprint; Fusion; Thermodynamic equilibrium; Solver","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":[0.0009482123,0.002886551,0.001617122,0.003483722,0.000893856,0.002007475,0.003863152,0.002784587,0.02642082],"category_scores_gemma":[0.004468036,0.0007918028,0.001495996,0.005851355,0.0004843962,0.002049065,0.001777793,0.002763932,0.0645822],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001392349,"about_ca_system_score_gemma":0.001762647,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01282415,"about_ca_topic_score_gemma":0.02134765,"domain_scores_codex":[0.9988387,0.0001508651,0.0001449263,0.0004123352,0.0003023765,0.0001509234],"domain_scores_gemma":[0.9984968,0.0002832101,0.0001588818,0.0005505533,0.0003653073,0.0001453109],"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":[0.0001775236,0.00009087708,0.001534068,0.0009803678,0.00008816882,0.00006510841,0.00003947556,0.002601485,0.0006118314,0.001562953,0.9872183,0.005029941],"study_design_scores_gemma":[0.0002878722,0.00004130042,0.00428557,0.0001850356,0.00005786187,0.0001317936,0.00008799177,0.003816714,0.001668955,0.003510412,0.9858711,0.00005526829],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0005036966,0.000100545,0.0003501481,0.00007392159,0.00003278455,0.00002213538,0.9964671,0.001664879,0.0007847011],"genre_scores_gemma":[0.0006092237,0.0000446891,0.0005956607,0.00002979544,0.000004173963,0.00005968281,0.9982608,0.0001052965,0.0002907556],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.02642082,"threshold_uncertainty_score":0.08838648,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03968022406021394,"score_gpt":0.2565467480729809,"score_spread":0.216866524012767,"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."}}