{"id":"W1604555343","doi":"10.1016/s0076-6879(00)28399-7","title":"[14] Detection of protein-protein interactions by protein fragment complementation strategies","year":2000,"lang":"en","type":"article","venue":"Methods in enzymology on CD-ROM/Methods in enzymology","topic":"Protein Structure and Dynamics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":139,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"Fragment (logic); Complementation; Protein-fragment complementation assay; Chemistry; Computational biology; Biology; Computer science; Biochemistry; Gene; Algorithm","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":[0.003317363,0.0006246764,0.0009561827,0.0005484834,0.0001485429,0.00003128919,0.0006127408,0.000937305,0.0005354412],"category_scores_gemma":[0.0007115465,0.0006510863,0.000212194,0.0006202799,0.0005839086,0.00004069634,0.0001911484,0.001055284,0.00001161841],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001968047,"about_ca_system_score_gemma":0.0001658191,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006139658,"about_ca_topic_score_gemma":0.001680874,"domain_scores_codex":[0.989371,0.006813984,0.001461061,0.001243262,0.0002405428,0.0008701304],"domain_scores_gemma":[0.9979133,0.0003342309,0.000542184,0.0009438159,0.0001441053,0.0001223422],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0008757236,0.0003724321,0.0001906059,0.00006897476,0.00008393783,0.00001750427,0.0001838125,0.0005398564,0.876959,0.002242605,0.00003808937,0.1184274],"study_design_scores_gemma":[0.002180091,0.002321739,0.005566787,0.00009994883,0.00003137662,0.0001018468,0.0003523957,0.0001923042,0.9395024,0.03794717,0.01105901,0.0006449214],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.707396,0.0005736103,0.2876829,0.0001660993,0.0003724184,0.001783359,0.00004798374,0.00004174215,0.001935924],"genre_scores_gemma":[0.5120377,0.00003952894,0.4857727,0.0001980723,0.0000999206,0.0009633134,0.0001195796,0.00005568268,0.0007135406],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1980898,"threshold_uncertainty_score":0.999594,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02301393693457959,"score_gpt":0.3946616965466323,"score_spread":0.3716477596120527,"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."}}