{"id":"W4385270969","doi":"10.12688/f1000research.133479.2","title":"The identification of high-performing antibodies for Coiled-coil-helix-coiled-coil-helix domain containing protein 10 (CHCHD10) for use in Western Blot, immunoprecipitation and immunofluorescence","year":2023,"lang":"en","type":"preprint","venue":"F1000Research","topic":"Amyotrophic Lateral Sclerosis Research","field":"Medicine","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Montreal Neurological Institute and Hospital","funders":"Canadian Institutes of Health Research; Genentech; Government of Canada; Ontario Genomics Institute; European Federation of Pharmaceutical Industries and Associations; Merck KGaA; Mitacs; Ontario Genomics; Genome Canada; Bayer; Motor Neurone Disease Association; Pfizer; Bristol-Myers Squibb","keywords":"Immunoprecipitation; Western blot; Antibody; Immunofluorescence; Coiled coil; Biology; Blot; Cell biology; Molecular biology; Gene; Genetics","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.008168262,0.0005857397,0.001172911,0.0008786764,0.0007399005,0.0006646855,0.001076546,0.0006343991,0.00003355745],"category_scores_gemma":[0.0059457,0.0004688601,0.0002940559,0.0006112776,0.0009462982,0.0004985147,0.00155531,0.001584518,0.00004538334],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000643444,"about_ca_system_score_gemma":0.0008599846,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004574639,"about_ca_topic_score_gemma":0.001173386,"domain_scores_codex":[0.992728,0.0006215577,0.002107375,0.001320598,0.001793251,0.001429198],"domain_scores_gemma":[0.9910181,0.003762627,0.0007658799,0.001517,0.002709748,0.0002266883],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.01969249,0.0005289996,0.03653213,0.008800726,0.0009138627,0.00004511202,0.006152617,0.0003931242,0.8860543,0.001264824,0.001640482,0.03798138],"study_design_scores_gemma":[0.01381973,0.00352284,0.8141438,0.01228951,0.0002710506,0.00002847523,0.003881443,0.03612169,0.09960256,0.01227699,0.002549697,0.00149221],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9806985,0.001458731,0.00150481,0.003226216,0.000339798,0.0120796,0.0005433372,0.0001303522,0.00001863213],"genre_scores_gemma":[0.9741738,0.002892462,0.004323524,0.00002758254,0.0003125492,0.007862956,0.0009616761,0.0002471925,0.009198236],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7864517,"threshold_uncertainty_score":0.9997763,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08249040749477722,"score_gpt":0.3702383076021669,"score_spread":0.2877479001073897,"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."}}