{"id":"W2335791358","doi":"10.1385/1592598536","title":"Laser Capture Microdissection","year":2005,"lang":"en","type":"book","venue":"Humana Press eBooks","topic":"Molecular Biology Techniques and Applications","field":"Biochemistry, Genetics and Molecular Biology","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Uniformed Services University of the Health Sciences; School of Medicine, New York University; Université Pierre et Marie Curie; Aarhus Universitetshospital; Universität Regensburg; Karolinska Institutet; Institut National de la Santé et de la Recherche Médicale; Brigham and Women's Hospital; University of Aberdeen; Universität Basel; Yale University; Institute of Genetics; Directorate for Biological Sciences; Alvin J. Siteman Cancer Center; Aarhus Universitet","keywords":"Laser capture microdissection; Microdissection; Laser; Computer science; Biology; Optics; Physics; Genetics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005482683,0.0006761251,0.0008483272,0.001685146,0.0009243838,0.001249035,0.001545857,0.000795208,0.03841424],"category_scores_gemma":[0.0004608899,0.0002993131,0.0004967556,0.001508178,0.0003993642,0.0006007889,0.00104269,0.001098172,0.03893911],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005098634,"about_ca_system_score_gemma":0.0005120902,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001046203,"about_ca_topic_score_gemma":0.00288831,"domain_scores_codex":[0.9992558,0.00004296294,0.00003309964,0.0002687551,0.0003478809,0.00005153823],"domain_scores_gemma":[0.9997255,0.00007600847,0.00001811162,0.00006390363,0.00008344204,0.00003302953],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001277719,0.0001034207,0.0005534302,0.001039896,0.00004326365,0.0005660117,0.0002143953,0.0008831389,0.4878592,0.01326639,0.08088236,0.4144606],"study_design_scores_gemma":[0.00002963204,0.0001405033,0.002087837,0.0001182941,0.00004272849,0.002228084,0.00003876238,0.002041848,0.09849837,0.00307811,0.8916347,0.00006114472],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01526186,0.03647868,0.6554555,0.001425621,0.002312564,0.002351276,0.01292889,0.01070657,0.2630791],"genre_scores_gemma":[0.03689562,0.02191613,0.4261907,0.001805414,0.0004604563,0.003078577,0.01018278,0.001004171,0.4984662],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.03841424,"threshold_uncertainty_score":0.1285084,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01704488232990885,"score_gpt":0.260005495165756,"score_spread":0.2429606128358471,"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."}}