{"id":"W1979229208","doi":"10.5555/2025756.2025769","title":"Multimodal representations, indexing, unexpectedness and proteins","year":2011,"lang":"en","type":"article","venue":"International Conference Industrial, Engineering & Other Applications Applied Intelligent Systems","topic":"Advanced Text Analysis Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Ottawa","funders":"","keywords":"Modalities; Computer science; Search engine indexing; Human–computer interaction; Topology (electrical circuits); Artificial intelligence; Computational biology; Biology; Engineering","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":[0.0008269079,0.000463285,0.000503497,0.002178279,0.0006842708,0.002475232,0.0005471968,0.000896991,0.005273029],"category_scores_gemma":[0.005146838,0.0001822753,0.0004637338,0.002728122,0.000714321,0.002833809,0.001104041,0.0005727354,0.0009040573],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006770923,"about_ca_system_score_gemma":0.0004005017,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001073054,"about_ca_topic_score_gemma":0.001158912,"domain_scores_codex":[0.99951,0.0001078936,0.00004164261,0.0001451931,0.000122806,0.00007249237],"domain_scores_gemma":[0.9981275,0.0007700094,0.0004716679,0.0002328981,0.0002831224,0.0001148296],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.003013077,0.0004563309,0.02460505,0.001351911,0.0002914972,0.001695952,0.001744107,0.0296745,0.1451036,0.1364412,0.01548984,0.640133],"study_design_scores_gemma":[0.0001307515,0.0007830386,0.04772719,0.0002242055,0.0003548104,0.003173361,0.002195762,0.4415615,0.04281552,0.4390275,0.02178036,0.0002261317],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7244234,0.005680627,0.2418474,0.002511051,0.000354714,0.0001027349,0.003966767,0.001759996,0.01935337],"genre_scores_gemma":[0.9627054,0.0009686108,0.02944018,0.0001313794,0.0001694031,0.00005127993,0.001937021,0.00008488021,0.004511795],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005273029,"threshold_uncertainty_score":0.01763999,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07768854023297872,"score_gpt":0.2903790542009867,"score_spread":0.212690513968008,"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."}}