{"id":"W1563533525","doi":"10.1186/1755-8166-2-18","title":"Candidate metastasis suppressor genes uncovered by array comparative genomic hybridization in a mouse allograft model of prostate cancer","year":2009,"lang":"en","type":"article","venue":"Molecular Cytogenetics","topic":"Mechanisms of cancer metastasis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Vancouver General Hospital; University of British Columbia","funders":"National Institutes of Health; National Cancer Institute; T.J. Martell Foundation; U.S. Department of Defense","keywords":"Metastasis Suppressor Gene; Metastasis; Biology; Suppressor; Metastasis suppressor; Prostate cancer; Gene; Candidate gene; Cancer research; Comparative genomic hybridization; Tumor suppressor gene; Cancer; Genome; Chromosome; Genetics; Carcinogenesis","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":[0.0001870547,0.0004121354,0.0002986905,0.0007481474,0.0001335293,0.0002140879,0.000207215,0.0002449779,0.00132645],"category_scores_gemma":[0.0001715854,0.0001424783,0.0002487345,0.0002283649,0.0001950408,0.0001125302,0.0001642034,0.0004515542,0.0002124957],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002655344,"about_ca_system_score_gemma":0.0001695641,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004384151,"about_ca_topic_score_gemma":0.0009468379,"domain_scores_codex":[0.9998492,0.00001776561,0.000008154582,0.00004241992,0.00005686362,0.00002562191],"domain_scores_gemma":[0.9998637,0.00003833477,0.00004496066,0.00001310718,0.00001454785,0.00002526089],"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":[0.00008360023,0.00001735181,0.0005088291,0.00001268403,0.000003804437,0.00002948986,0.00000480266,0.00005447088,0.9986002,0.00002944686,0.00001350469,0.0006418731],"study_design_scores_gemma":[0.00003551042,0.0007879068,0.02309618,0.000005769935,0.00006647678,0.0009452153,0.00003117493,0.002262273,0.970933,0.0001477315,0.001679474,0.000009254174],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.991666,0.0005974103,0.006624871,0.00006131615,0.00001039905,0.00002386944,0.0004300394,0.0001291065,0.0004570302],"genre_scores_gemma":[0.9869025,0.0006174201,0.008634336,0.0000516961,0.000008600147,0.00006642793,0.001675161,0.00003300051,0.002010796],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00132645,"threshold_uncertainty_score":0.004437387,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01799459896948114,"score_gpt":0.2759226671438239,"score_spread":0.2579280681743427,"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."}}