{"id":"W4412825786","doi":"10.1093/bib/bbaf372","title":"ConvNTC: convolutional neural tensor completion for detecting “A–A–B” type biological triplets","year":2025,"lang":"en","type":"article","venue":"Briefings in Bioinformatics","topic":"Tensor decomposition and applications","field":"Mathematics","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Multilinear map; Tensor (intrinsic definition); Computer science; Convolutional neural network; Artificial intelligence; Tensor algebra; Context (archaeology); Nonlinear system; Theoretical computer science; Pattern recognition (psychology); Mathematics; Algebra over a field; Physics; Pure mathematics; Biology","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001765196,0.002753868,0.001338809,0.001500641,0.0006923404,0.0009930823,0.002584911,0.001366927,0.003059832],"category_scores_gemma":[0.00440842,0.0006851873,0.001970376,0.001329818,0.00105518,0.002029895,0.001616518,0.002940178,0.001974696],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001962419,"about_ca_system_score_gemma":0.002525886,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02563329,"about_ca_topic_score_gemma":0.02968026,"domain_scores_codex":[0.9990203,0.0001970098,0.00006079553,0.0003361795,0.0002470883,0.0001386272],"domain_scores_gemma":[0.9982992,0.0003233662,0.0002925924,0.0004572532,0.000455527,0.0001719929],"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":[0.0008814005,0.0005040965,0.006640625,0.0006918034,0.0005247536,0.0005978535,0.0002311488,0.3835665,0.05331088,0.0202535,0.06706227,0.4657352],"study_design_scores_gemma":[0.00001298865,0.00004442777,0.0004137411,0.00001249851,0.00001951623,0.00006757597,0.00001613625,0.9865122,0.005699543,0.004989692,0.002193093,0.00001868314],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.05916227,0.001914156,0.9149256,0.0006552351,0.0002737918,0.0002575317,0.003352517,0.01612446,0.003334444],"genre_scores_gemma":[0.4131629,0.001283055,0.5515767,0.0006760852,0.0001434613,0.0003746286,0.02200402,0.001188412,0.009590666],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02563329,"threshold_uncertainty_score":0.05096817,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08588467673509687,"score_gpt":0.3492596114861307,"score_spread":0.2633749347510339,"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."}}