{"id":"W4401042441","doi":"10.18653/v1/2024.naacl-long.350","title":"ContraSim – Analyzing Neural Representations Based on Contrastive Learning","year":2024,"lang":"en","type":"article","venue":"","topic":"Neural Networks and Applications","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Azrieli Foundation; Open Philanthropy Project","keywords":"Computer science; Artificial intelligence; Artificial neural network; Natural language processing","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.0009741492,0.0006867877,0.000683939,0.0009582968,0.0003868181,0.001760326,0.001532949,0.0008991156,0.003884069],"category_scores_gemma":[0.00548255,0.0003755494,0.0007212455,0.000782351,0.001008153,0.003401677,0.001506286,0.001723795,0.0008273062],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004647377,"about_ca_system_score_gemma":0.0003875655,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001894424,"about_ca_topic_score_gemma":0.001746669,"domain_scores_codex":[0.9996985,0.0001001232,0.0000188149,0.00008887864,0.00006098824,0.00003270414],"domain_scores_gemma":[0.998904,0.000620164,0.0001150578,0.0001650872,0.0001445779,0.00005119613],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0005899954,0.0001955334,0.003109606,0.0004885476,0.0003057632,0.0003010822,0.0004633215,0.1262591,0.03234961,0.1711818,0.01540423,0.6493514],"study_design_scores_gemma":[0.00001710581,0.00007967748,0.0007908799,0.00002472942,0.00002900173,0.0001170135,0.00004541003,0.8785378,0.005377212,0.1127601,0.002195616,0.00002543946],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.06439802,0.003418058,0.9235727,0.001201236,0.0004193641,0.0000560748,0.000228458,0.0009523125,0.005753826],"genre_scores_gemma":[0.8409905,0.001457007,0.1491861,0.0003374217,0.0003273677,0.0001061916,0.0007350279,0.000379306,0.006481102],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003884069,"threshold_uncertainty_score":0.01299351,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01467403081603912,"score_gpt":0.2851852182575468,"score_spread":0.2705111874415077,"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."}}