{"id":"W4281634317","doi":"10.5281/zenodo.6604047","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":"Antibody; Characterization (materials science); Computational biology; Medicine; Biology; Immunology; Materials science; 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":[0.0007912227,0.002133257,0.0009855466,0.002683014,0.001006806,0.0008730781,0.001761813,0.0008752933,0.04621599],"category_scores_gemma":[0.001885058,0.0008569154,0.001291041,0.001832558,0.0002347185,0.0008333391,0.0006941259,0.001640061,0.03668191],"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":0.002217958,"about_ca_topic_score_gemma":0.0031461,"domain_scores_codex":[0.9988907,0.0001725619,0.0001423381,0.0002582887,0.0003131168,0.0002229907],"domain_scores_gemma":[0.998485,0.00026476,0.0001612044,0.0002442354,0.0005892187,0.0002557023],"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":[0.001171767,0.0002262773,0.0007016716,0.001506657,0.0001306233,0.001007585,0.0001490073,0.0003613179,0.8937966,0.001968115,0.04357913,0.0554013],"study_design_scores_gemma":[0.000220525,0.0009152318,0.007695861,0.0002746047,0.000299481,0.005481183,0.00009223965,0.001149647,0.2967122,0.0007877842,0.6862918,0.00007951107],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"dataset","genre_scores_codex":[0.2401386,0.09450051,0.3186932,0.006979391,0.009939401,0.007091765,0.1340355,0.007637993,0.1809837],"genre_scores_gemma":[0.1833516,0.04781858,0.1515758,0.003620007,0.002239973,0.004067578,0.4704197,0.001360286,0.1355465],"genre_candidate":"dataset","genre_consensus":null,"teacher_disagreement_score":0.04621599,"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."}}