{"id":"W2067237567","doi":"10.1101/gr.6667007","title":"Examining protein–protein interactions using endogenously tagged yeast arrays: The Cross-and-Capture system","year":2007,"lang":"en","type":"article","venue":"Genome Research","topic":"Bioinformatics and Genomic Networks","field":"Biochemistry, Genetics and Molecular Biology","cited_by":28,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"National Cancer Institute; Genentech; Canadian Institutes of Health Research; Genome Canada; Gebert Rüf Stiftung; Ontario Genomics; Ontario Genomics Institute","keywords":"Biology; Yeast; Computational biology; Protein–protein interaction; Protein-fragment complementation assay; Saccharomyces cerevisiae; Function (biology); Genetics; DNA; Two-hybrid screening; Protein function; Gene; Phenotype","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006049601,0.0009789417,0.000765316,0.0005685707,0.0004568835,0.0008001774,0.0006968772,0.0008865854,0.001249086],"category_scores_gemma":[0.0004683685,0.0004271967,0.0004745543,0.0004231018,0.0004110634,0.0004544179,0.0008792083,0.001329457,0.0009313723],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003781697,"about_ca_system_score_gemma":0.0002136228,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005402559,"about_ca_topic_score_gemma":0.001056229,"domain_scores_codex":[0.9992377,0.0001426664,0.00004313907,0.0002368991,0.0002578952,0.0000817584],"domain_scores_gemma":[0.9995406,0.0001427253,0.00009004983,0.00008124075,0.00007631396,0.00006910032],"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":[0.00002927233,0.00001994304,0.0002561427,0.00003045844,0.00001999005,0.00001883865,0.000008355191,0.00007026815,0.997331,0.0001137939,0.0001010533,0.002000831],"study_design_scores_gemma":[0.000005827629,0.00008796106,0.001862996,0.000002589707,0.00002043644,0.0002792247,0.00001138629,0.002432175,0.9938071,0.00009810735,0.001378338,0.00001378146],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.5344915,0.004281677,0.4528046,0.0005606845,0.0001887636,0.0002382005,0.001339563,0.002670492,0.003424442],"genre_scores_gemma":[0.7662256,0.003291041,0.2207208,0.0008282435,0.00006710189,0.0005091039,0.002751504,0.0002183048,0.005388279],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.001249086,"threshold_uncertainty_score":0.004178584,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0812405280705566,"score_gpt":0.341900187407472,"score_spread":0.2606596593369154,"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."}}