{"id":"W2418298802","doi":"10.1007/978-1-4939-3393-8_11","title":"Laser Capture Microdissection: Avoiding Bias in Analysis by Selecting Just What Matters","year":2016,"lang":"en","type":"article","venue":"Methods in molecular biology","topic":"Molecular Biology Techniques and Applications","field":"Biochemistry, Genetics and Molecular Biology","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"","keywords":"Laser capture microdissection; Microdissection; Homogeneous; Identification (biology); Population; Biology; Computational biology; Plant tissue; Biological system; Computer science; Genetics; Gene; Botany; Gene expression; Mathematics","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":[0.007015489,0.0006616149,0.001735139,0.000903161,0.001571667,0.002491602,0.001119108,0.001573074,0.001380649],"category_scores_gemma":[0.00969412,0.0006541955,0.0004078664,0.001372741,0.001483788,0.001608645,0.001141567,0.001567131,0.0008600656],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006028205,"about_ca_system_score_gemma":0.00140044,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006482648,"about_ca_topic_score_gemma":0.003397668,"domain_scores_codex":[0.9941424,0.001647063,0.0004427083,0.001376965,0.002114947,0.0002759266],"domain_scores_gemma":[0.9888316,0.006751063,0.0009347665,0.001684588,0.001464572,0.0003333577],"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":[0.0004057573,0.0001208902,0.006011434,0.0007626223,0.0001635257,0.0002148259,0.0003716196,0.0005645941,0.901631,0.004521217,0.004122697,0.08110984],"study_design_scores_gemma":[0.0001306854,0.000213043,0.02409355,0.0001342754,0.0004528061,0.001350112,0.0002684139,0.01485826,0.9105461,0.01794254,0.02984917,0.0001609706],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2177476,0.01003965,0.755002,0.003453645,0.001253324,0.0005217528,0.0008089878,0.002167269,0.009005794],"genre_scores_gemma":[0.4249697,0.005174033,0.5531465,0.005783239,0.0008745273,0.001015205,0.000989774,0.00202765,0.006019479],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.007015489,"threshold_uncertainty_score":0.03710186,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02360604092300802,"score_gpt":0.3839637700744522,"score_spread":0.3603577291514442,"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."}}