{"id":"W2025428992","doi":"10.1016/j.cbd.2007.10.001","title":"Microarray analysis reveals differences in expression of cell surface and extracellular matrix components during development of the trout ovary and testis","year":2007,"lang":"en","type":"article","venue":"Comparative Biochemistry and Physiology Part D Genomics and Proteomics","topic":"Reproductive biology and impacts on aquatic species","field":"Biochemistry, Genetics and Molecular Biology","cited_by":14,"is_retracted":false,"has_abstract":false,"ca_institutions":"Simon Fraser University; University of Victoria","funders":"Natural Sciences and Engineering Research Council of Canada; Genome British Columbia; Genome Canada","keywords":"Biology; Extracellular matrix; Cell biology; Transcriptome; Microarray analysis techniques; Gene expression; Angiogenesis; Trout; 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":[],"consensus_categories":[],"category_scores_codex":[0.0002895154,0.0001745473,0.0003874346,0.00003109655,0.0001185851,0.000006871924,0.0000948084,0.0001579966,0.000002114077],"category_scores_gemma":[0.00002370126,0.0001311699,0.00003525276,0.00008058714,0.0005708332,0.000004974544,0.0001776743,0.0001005931,5.899841e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000008003543,"about_ca_system_score_gemma":0.00003112771,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005470548,"about_ca_topic_score_gemma":0.000004343511,"domain_scores_codex":[0.9989769,0.00008047387,0.0003584498,0.0003840349,0.0000395397,0.0001605495],"domain_scores_gemma":[0.9993915,0.00005021292,0.000263474,0.000196025,0.00004261068,0.00005615502],"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":[0.0002855273,0.00004571404,0.1753284,0.00008432189,0.00007433348,1.665535e-7,0.0004800349,0.000008805494,0.8236663,0.000004584685,0.000002325695,0.00001954721],"study_design_scores_gemma":[0.0002569216,0.00003576504,0.4053083,0.00001667741,0.00002183016,0.000002937098,0.0001860525,0.00001753519,0.5940082,0.00003910799,0.00002029239,0.00008636822],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9928461,0.006665713,0.0001788487,0.0000136649,0.00002150071,0.0002273144,0.00002931376,0.000001349199,0.00001613947],"genre_scores_gemma":[0.995271,0.0004636623,0.004088999,0.000004906843,0.00002698574,0.000004379217,0.00003147939,0.000004451411,0.0001041176],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2299799,"threshold_uncertainty_score":0.5348952,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02587223605094795,"score_gpt":0.2631874324233307,"score_spread":0.2373151963723827,"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."}}