{"id":"W3004207757","doi":"10.1145/3366423.3380061","title":"NCVis: Noise Contrastive Approach for Scalable Visualization","year":2020,"lang":"en","type":"preprint","venue":"","topic":"Music and Audio Processing","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Optech (Canada)","funders":"","keywords":"Computer science; Dimensionality reduction; Visualization; Scalability; Noise (video); Representation (politics); Curse of dimensionality; Software; Noise reduction; Data mining; Artificial intelligence; Image (mathematics); Database","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":[0.0002001033,0.0002229217,0.0003180432,0.00006089264,0.0001254046,0.0005200165,0.0008260263,0.0001749123,0.00001463104],"category_scores_gemma":[0.00008149998,0.0001983585,0.0001076382,0.0001966209,0.00003191108,0.0002520123,0.0008692099,0.0001861849,0.00001194431],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004163296,"about_ca_system_score_gemma":0.0002552481,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001383628,"about_ca_topic_score_gemma":4.342251e-7,"domain_scores_codex":[0.9984242,0.00003307466,0.0002672672,0.000804973,0.000222809,0.000247722],"domain_scores_gemma":[0.9991027,0.00005374416,0.0001983944,0.0003340392,0.0002030163,0.0001081239],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00007890477,0.0005508668,0.0002304252,0.004521128,0.0003179527,0.000008420633,0.006157717,0.0159579,0.002605386,0.6601274,0.1483736,0.1610702],"study_design_scores_gemma":[0.0002917922,0.00002803727,0.00004669587,0.00006615889,0.00001892664,0.000001203852,0.00003125189,0.9793703,0.003042875,0.01427423,0.002538038,0.000290468],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00005214157,0.000141191,0.9795511,0.001161453,0.0003364666,0.0006409563,0.000009215912,0.0003843653,0.01772312],"genre_scores_gemma":[0.2278523,0.00001402275,0.7654889,0.004420067,0.0004753879,0.0002811605,0.0001448605,0.00003092567,0.00129235],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9634124,"threshold_uncertainty_score":0.8088824,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04518701707255766,"score_gpt":0.2905555323014588,"score_spread":0.2453685152289011,"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."}}