{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00006724532,0.0003243334,0.000212994,0.00004563534,0.0001167776,0.00002919089,0.0003341425,0.0008813704,0.00004114872],"category_scores_gemma":[0.000004022225,0.0003283123,0.0001986871,0.000004596765,0.000130776,8.329534e-7,0.0001770003,0.0003058306,0.00001813414],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000323927,"about_ca_system_score_gemma":0.00008996815,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002579052,"about_ca_topic_score_gemma":0.0001070035,"domain_scores_codex":[0.9988109,0.00003272613,0.0002337193,0.0005889673,0.00009515589,0.0002385654],"domain_scores_gemma":[0.998933,0.000003251671,0.0001587262,0.0007563399,0.00007620289,0.0000725429],"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":[0.00003106719,0.00004655094,5.737284e-7,0.00005790847,0.0002324806,0.00001050143,0.00003682576,0.000006394993,0.05620059,0.01057083,0.8823637,0.05044259],"study_design_scores_gemma":[0.000135691,0.00005936487,0.000002759002,0.00002440046,0.00006261594,0.00002186448,0.000001284664,0.000003180938,0.07119908,0.0002884911,0.9278712,0.0003300969],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.000211935,0.006253508,0.001974074,0.00002151292,0.0001037897,0.0005774894,0.0001113406,0.00009132571,0.990655],"genre_scores_gemma":[0.001638319,0.0006993934,0.0007324544,0.0005464762,0.001097848,0.0002167182,0.001648013,0.00008841591,0.9933324],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.05011249,"threshold_uncertainty_score":0.9999169,"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."}}