{"id":"W4393573526","doi":"10.5281/zenodo.10404173","title":"Data for An Approximate Skolem Funcion Counter (AAAI-24 paper)","year":2024,"lang":"en","type":"dataset","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Parallel Computing and Optimization Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"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":[0.00142526,0.003762472,0.001697355,0.003222506,0.001280817,0.002779081,0.003656763,0.003880248,0.04877001],"category_scores_gemma":[0.006868158,0.0008351695,0.001772967,0.006166335,0.0007219487,0.001654513,0.001932331,0.002782482,0.1087318],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001835467,"about_ca_system_score_gemma":0.002566835,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01181531,"about_ca_topic_score_gemma":0.02094801,"domain_scores_codex":[0.9976972,0.0002802859,0.000250171,0.0005225245,0.0009194648,0.000330347],"domain_scores_gemma":[0.995674,0.0006658414,0.000297559,0.001702762,0.001332508,0.0003274105],"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":[0.0001834772,0.00006755861,0.0006611553,0.0005046256,0.00002480859,0.00003209411,0.000009847447,0.0009469358,0.0002830606,0.0005791357,0.9929914,0.003715925],"study_design_scores_gemma":[0.0007434711,0.00009527689,0.004147748,0.0001665808,0.00004097351,0.0001598832,0.00005117622,0.003130512,0.003020928,0.003543254,0.9848515,0.00004865669],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0006336879,0.0001620842,0.0002760611,0.0001162618,0.0001058462,0.00002659233,0.9947578,0.002133941,0.001787561],"genre_scores_gemma":[0.001124053,0.00004430286,0.0005675305,0.00005095038,0.00001481011,0.00007370622,0.997311,0.0001518729,0.0006617438],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.04877001,"threshold_uncertainty_score":0.1631519,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07655243855782126,"score_gpt":0.2997075183814828,"score_spread":0.2231550798236615,"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."}}