{"id":"W4220991263","doi":"10.5281/zenodo.6370607","title":"Antibody Characterization Report for Hamartin","year":2022,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Monoclonal and Polyclonal Antibodies Research","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Montreal Neurological Institute and Hospital","funders":"","keywords":"Characterization (materials science); Antibody; Computational biology; Computer science; Medicine; Biology; Materials science; Immunology; Nanotechnology","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":[0.000791222,0.002133255,0.0009855448,0.002683012,0.001006804,0.0008730774,0.001761812,0.0008752925,0.04621597],"category_scores_gemma":[0.001885058,0.0008569142,0.00129104,0.001832557,0.0002347183,0.0008333384,0.0006941252,0.001640058,0.03668186],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000798089,"about_ca_system_score_gemma":0.001279585,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002217957,"about_ca_topic_score_gemma":0.003146099,"domain_scores_codex":[0.9988907,0.0001725622,0.0001423381,0.0002582882,0.0003131168,0.0002229907],"domain_scores_gemma":[0.998485,0.00026476,0.0001612041,0.000244235,0.0005892182,0.0002557021],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001171766,0.0002262771,0.0007016713,0.001506655,0.0001306231,0.001007585,0.0001490072,0.0003613179,0.8937966,0.001968114,0.0435791,0.05540134],"study_design_scores_gemma":[0.0002205245,0.0009152318,0.007695864,0.000274604,0.0002994805,0.00548118,0.00009223958,0.001149645,0.2967119,0.0007877828,0.6862921,0.00007951095],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"dataset","genre_scores_codex":[0.2401389,0.09450056,0.3186926,0.006979385,0.009939405,0.007091757,0.1340355,0.007637976,0.1809839],"genre_scores_gemma":[0.1833519,0.04781858,0.1515756,0.003620004,0.002239974,0.004067571,0.4704196,0.001360281,0.1355467],"genre_candidate":"dataset","genre_consensus":null,"teacher_disagreement_score":0.04621597,"threshold_uncertainty_score":0.1546078,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04090382929977857,"score_gpt":0.3040413118437129,"score_spread":0.2631374825439343,"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."}}