{"id":"W3109258702","doi":"","title":"Scaling up Simhash","year":2020,"lang":"en","type":"article","venue":"Asian Conference on Machine Learning","topic":"Quantum Computing Algorithms and Architecture","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University; University of Waterloo","funders":"","keywords":"Scaling; Computer science; Mathematics; Geometry","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001922969,0.0002292869,0.0002341136,0.00007493493,0.0003186277,0.0003563478,0.0009437639,0.00006360486,0.00007945702],"category_scores_gemma":[0.000235047,0.0002041928,0.00008769627,0.0003848642,0.00003641905,0.0001421315,0.0003274978,0.0009489728,0.0002810966],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001232078,"about_ca_system_score_gemma":0.00006897982,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001787883,"about_ca_topic_score_gemma":0.000001415983,"domain_scores_codex":[0.9983038,0.0001737049,0.0002205354,0.0005951974,0.0003180351,0.0003887491],"domain_scores_gemma":[0.9991803,0.0001050173,0.0001149443,0.0002966459,0.00005215958,0.0002509566],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001013407,0.00001818903,0.000673386,0.0000175839,0.00001528014,0.00005272736,0.003847993,0.01583753,0.0004133406,0.04424969,0.0001185573,0.9347456],"study_design_scores_gemma":[0.0002928831,0.0002117921,0.000746392,0.00004835226,0.000003001708,0.00001209021,0.00007096229,0.9881257,0.0002020915,0.001059416,0.008971668,0.0002556805],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0361581,0.00009645266,0.8860505,0.05137762,0.0005153082,0.0001767502,0.000002700172,0.001337068,0.02428546],"genre_scores_gemma":[0.9813383,0.000006575407,0.01620562,0.001988026,0.0002106585,0.000002424593,0.000005323492,0.00001904615,0.0002240262],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9722881,"threshold_uncertainty_score":0.8326739,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02536517655840875,"score_gpt":0.2523355812988393,"score_spread":0.2269704047404306,"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."}}