{"id":"W1581044219","doi":"10.1002/9780813807379.ch4","title":"Aquaculture‐Related Applications of DNA Microarray Technology","year":2009,"lang":"en","type":"other","venue":"","topic":"Aquaculture disease management and microbiota","field":"Immunology and Microbiology","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Public Health Agency of Canada; Fisheries and Oceans Canada; Institute for Marine Biosciences; Memorial University of Newfoundland","funders":"","keywords":"Microarray; Aquaculture; Biology; DNA microarray; Zebrafish; Gene chip analysis; Microarray analysis techniques; Fish <Actinopterygii>; Computational biology; Fishery; Genetics; Gene; Gene expression","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":[0.001370898,0.0008695385,0.000716917,0.002542695,0.0006857615,0.00149057,0.001219247,0.001259526,0.03332247],"category_scores_gemma":[0.001003553,0.0004676779,0.0007583943,0.002750211,0.0004869718,0.001179372,0.001348641,0.001451963,0.0180275],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001024332,"about_ca_system_score_gemma":0.0007921117,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001053557,"about_ca_topic_score_gemma":0.001990386,"domain_scores_codex":[0.9988064,0.0002030775,0.00006502753,0.0002246508,0.0006368078,0.00006408669],"domain_scores_gemma":[0.9994509,0.0002145102,0.00003522217,0.00007117211,0.0001822194,0.00004599654],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000125752,0.0002001064,0.000802168,0.001852992,0.00004099749,0.0003726632,0.0001898768,0.0009164804,0.3252101,0.01691865,0.08096404,0.5724061],"study_design_scores_gemma":[0.00001400624,0.0001060701,0.001676408,0.0002234602,0.00002219974,0.0006685313,0.0001069327,0.0008252081,0.09436662,0.005234064,0.8967204,0.00003615814],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.0118869,0.1089772,0.3372479,0.01181959,0.006883149,0.001286413,0.008902216,0.004691415,0.5083052],"genre_scores_gemma":[0.03738581,0.1902436,0.4043501,0.00774532,0.003183708,0.001411282,0.01054982,0.0007176732,0.3444127],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.03332247,"threshold_uncertainty_score":0.1114748,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003609599939825637,"score_gpt":0.2115383512202247,"score_spread":0.2079287512803991,"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."}}