{"id":"W4415933323","doi":"10.1021/acsomega.5c07055","title":"Half-Space Proximal Networks (HSPNs): A Proxy for Multi-Query Similarity Searching Models Predicting Tumor-Homing Peptides","year":2025,"lang":"en","type":"article","venue":"ACS Omega","topic":"Machine Learning in Bioinformatics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Universidad San Francisco de Quito; Universitat de València","keywords":"Leverage (statistics); Similarity (geometry); Centrality; Pairwise comparison; Benchmarking; Pattern recognition (psychology); Artificial neural network; Proxy (statistics)","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0008608748,0.0002740521,0.0002618722,0.00009786644,0.0003801212,0.0001419292,0.0004031409,0.0002112811,6.065939e-7],"category_scores_gemma":[0.0008631143,0.0002690699,0.0001348314,0.0001710755,0.00009314944,0.00003070721,0.0004620002,0.0004558142,0.000001276633],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004294994,"about_ca_system_score_gemma":0.0001708163,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005367797,"about_ca_topic_score_gemma":0.00005272265,"domain_scores_codex":[0.9983055,0.00009191125,0.0004185782,0.0004340959,0.0001678064,0.0005821282],"domain_scores_gemma":[0.9989794,0.0001070525,0.000185098,0.0004721619,0.0001677079,0.00008857378],"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":[0.001847406,0.0009220446,0.206688,0.003954391,0.001332567,0.00002893744,0.003450187,0.5876225,0.1421354,0.01288788,0.0149218,0.02420887],"study_design_scores_gemma":[0.001079718,0.0001670472,0.0007571514,0.0001693941,0.00004038375,0.00001160944,0.000233487,0.9787546,0.01252837,0.0002417432,0.005704419,0.0003120354],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5337,0.0004345574,0.4613036,0.0004520332,0.0002074263,0.001297328,0.00002143743,0.000108278,0.002475308],"genre_scores_gemma":[0.9193583,0.00003019796,0.07811469,0.00054661,0.0002477231,0.0001856769,0.0001310917,0.00004256376,0.001343123],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3911321,"threshold_uncertainty_score":0.9999762,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01776565920220402,"score_gpt":0.2960223005562391,"score_spread":0.2782566413540351,"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."}}