{"id":"W6929288060","doi":"10.48448/xk4m-dn57","title":"Recursive Neural Networks with Bottlenecks Diagnose (Non-)Compositionality","year":2022,"lang":"en","type":"other","venue":"Underline Science Inc.","topic":"Prenatal Screening and Diagnostics","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Principle of compositionality; Bottleneck; Information bottleneck method; Metric (unit); Artificial neural network; Ranking (information retrieval); Natural language","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":[0.003729978,0.001051646,0.000779013,0.001036638,0.0006692956,0.001491999,0.001309356,0.001085008,0.002313814],"category_scores_gemma":[0.02341043,0.0005718498,0.0006158118,0.0009573213,0.001611869,0.004145147,0.002402053,0.002340667,0.0005555885],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001367487,"about_ca_system_score_gemma":0.001146762,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00546614,"about_ca_topic_score_gemma":0.009548944,"domain_scores_codex":[0.9985544,0.0006246579,0.0000872168,0.0003256545,0.0002638237,0.0001442734],"domain_scores_gemma":[0.9906662,0.00591177,0.0008297732,0.001397394,0.0009985901,0.0001961779],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0008461827,0.0003126888,0.02379727,0.0005362259,0.0003214254,0.0006291976,0.001699837,0.4720128,0.03529569,0.09661032,0.005702769,0.3622356],"study_design_scores_gemma":[0.00001201803,0.00006341203,0.001571794,0.00002142303,0.00002604289,0.00005899833,0.0001089124,0.9452882,0.006885218,0.04485096,0.001096882,0.00001613642],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2661206,0.0006285681,0.7263525,0.0007930243,0.0000537088,0.00007479926,0.0004095295,0.002222387,0.003344897],"genre_scores_gemma":[0.853793,0.0002312975,0.1426531,0.000197391,0.00003940737,0.000134389,0.0008495647,0.0002907104,0.001811176],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00546614,"threshold_uncertainty_score":0.01972628,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0128866749576053,"score_gpt":0.2795446215318533,"score_spread":0.266657946574248,"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."}}