{"id":"W2104080300","doi":"10.1186/gb-2003-4-3-r23","title":"The GRID: The General Repository for Interaction Datasets","year":2003,"lang":"en","type":"article","venue":"Genome biology","topic":"Bioinformatics and Genomic Networks","field":"Biochemistry, Genetics and Molecular Biology","cited_by":299,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lunenfeld-Tanenbaum Research Institute; Mount Sinai Hospital","funders":"Canadian Institutes of Health Research; Canada Research Chairs","keywords":"Grid; Computer science; Parsing; Visualization; Genome browser; Information retrieval; Data mining; Biology; Genomics; Artificial intelligence; Genome; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005338038,0.002532762,0.003232306,0.007350264,0.001844542,0.006734328,0.00800647,0.001828542,0.02076839],"category_scores_gemma":[0.01453386,0.001955147,0.002455036,0.01278871,0.0008285361,0.006436056,0.008568014,0.004270746,0.03251621],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001358739,"about_ca_system_score_gemma":0.004844334,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006742984,"about_ca_topic_score_gemma":0.006735789,"domain_scores_codex":[0.9952302,0.0008776544,0.001093257,0.0009725349,0.001428851,0.0003974646],"domain_scores_gemma":[0.992137,0.00132932,0.0006977283,0.003795689,0.001104181,0.0009360343],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0007846814,0.0001498561,0.003864632,0.002002251,0.0004218196,0.0005233869,0.0004142365,0.006390823,0.006583228,0.04207239,0.8661748,0.07061781],"study_design_scores_gemma":[0.0003702535,0.00007258991,0.003811181,0.0003564794,0.0001924321,0.0006393525,0.0001723021,0.01621032,0.00709725,0.0522355,0.9186278,0.0002146661],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00264002,0.001409422,0.230359,0.001017818,0.0003051847,0.0006257233,0.6297833,0.1248483,0.009011223],"genre_scores_gemma":[0.008120289,0.0009808931,0.1013794,0.0003858583,0.00006872464,0.0008808742,0.8776046,0.008462008,0.002117376],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.02076839,"threshold_uncertainty_score":0.06947714,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009498871322888507,"score_gpt":0.2576102786892654,"score_spread":0.2481114073663769,"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."}}