{"id":"W4394487980","doi":"10.6084/m9.figshare.22229713","title":"Can-SWaP_V1","year":2023,"lang":"en","type":"dataset","venue":"Figshare","topic":"Parallel Computing and Optimization Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Swap (finance); Interest rate swap; Computer science; Business; Finance","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00005265899,0.000216172,0.0002061707,0.0002012203,0.0001041426,0.0002643537,0.002240078,0.0002478672,0.00618969],"category_scores_gemma":[0.0005423534,0.0002171931,0.00008769368,0.0004846557,0.000002931353,0.00008510984,0.001015603,0.0003099538,0.03369366],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004212874,"about_ca_system_score_gemma":0.0001651037,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006335657,"about_ca_topic_score_gemma":0.00002701342,"domain_scores_codex":[0.9987476,0.00004495954,0.0001933359,0.0004609961,0.000278602,0.0002744891],"domain_scores_gemma":[0.9984775,0.0001325574,0.0001591192,0.001037914,0.0001069143,0.0000860472],"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":[1.274777e-7,0.000006614868,1.538091e-8,0.00007417967,0.000006513303,0.0000400923,0.00000408759,0.0001324408,1.88406e-8,0.000006191086,0.9993052,0.0004244949],"study_design_scores_gemma":[0.0000359736,0.00001720996,0.000004932378,0.0007700426,0.00000208184,0.000005952948,2.547316e-7,0.003523994,0.00001003472,0.0001281514,0.995248,0.000253371],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[1.724599e-9,0.00006819695,0.000371268,0.0001922016,0.0002089901,0.0001341143,0.9974025,0.001408373,0.0002143141],"genre_scores_gemma":[1.266577e-7,0.0000195904,0.002373303,0.0004720444,0.0001689249,0.0001266137,0.9961729,0.00001563495,0.0006508813],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.02750397,"threshold_uncertainty_score":0.9947188,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0478446055144977,"score_gpt":0.2894698926460575,"score_spread":0.2416252871315598,"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."}}