{"id":"W6911840485","doi":"10.5281/zenodo.13085795","title":"Source Code of GearBind: Pretrainable Geometric Graph Neural Network for Antibody Affinity Maturation","year":2023,"lang":"en","type":"dataset","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"","field":"","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Mila - Quebec Artificial Intelligence Institute","funders":"","keywords":"Graph; Artificial neural network; In silico; Source code; Pattern recognition (psychology); Antibody; Code (set theory)","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":[0.0006669276,0.00502332,0.001351179,0.00152941,0.0005425939,0.001406807,0.004182395,0.002633926,0.03132204],"category_scores_gemma":[0.002559444,0.001118334,0.00167827,0.001749279,0.0005404163,0.001038474,0.001286608,0.002658215,0.03599743],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002093328,"about_ca_system_score_gemma":0.002010303,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0324932,"about_ca_topic_score_gemma":0.06734073,"domain_scores_codex":[0.9995658,0.00005570184,0.00003068129,0.000160912,0.0001232666,0.00006380476],"domain_scores_gemma":[0.9995099,0.0001630638,0.0000299251,0.000135807,0.0001241883,0.00003719046],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002713436,0.0001805434,0.001416895,0.000948527,0.0001725304,0.0001169985,0.00002397572,0.0306369,0.001037688,0.001053657,0.9321622,0.03197871],"study_design_scores_gemma":[0.002056586,0.0003293348,0.005209367,0.0003862603,0.0001658931,0.0006278775,0.00009381968,0.3077035,0.01156841,0.01915719,0.6525455,0.0001563172],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.007005981,0.001247126,0.01836283,0.000655939,0.0004026415,0.000390204,0.9107109,0.05462437,0.00660002],"genre_scores_gemma":[0.007965629,0.0002897744,0.01746591,0.0001956692,0.00001931814,0.0006843061,0.9682737,0.001400382,0.003705436],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.0324932,"threshold_uncertainty_score":0.1047826,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04198859295743699,"score_gpt":0.2821841034636695,"score_spread":0.2401955105062325,"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."}}