{"id":"W4382345223","doi":"10.1371/journal.pbio.3002167","title":"A biologist’s guide to planning and performing quantitative bioimaging experiments","year":2023,"lang":"en","type":"article","venue":"PLoS Biology","topic":"Cell Image Analysis Techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":31,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"National Institutes of Health; National Institute of General Medical Sciences; Chan Zuckerberg Initiative; European Molecular Biology Laboratory; Silicon Valley Community Foundation","keywords":"Data science; Biology; Plan (archaeology); Sample (material); Quantitative analysis (chemistry); Interpretation (philosophy); Computer science; Management science; Engineering","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":[0.01165047,0.00286492,0.002613911,0.005170694,0.002069763,0.003329081,0.004894864,0.003506202,0.04726128],"category_scores_gemma":[0.01428117,0.003132768,0.001783628,0.003543893,0.003180359,0.003780853,0.002699398,0.01140264,0.06651487],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002083586,"about_ca_system_score_gemma":0.007690249,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003251429,"about_ca_topic_score_gemma":0.01068131,"domain_scores_codex":[0.9941745,0.001571886,0.0006311825,0.0007245178,0.002624989,0.0002729011],"domain_scores_gemma":[0.9850788,0.005290478,0.0007879476,0.002800083,0.005099272,0.0009434113],"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":[0.0001322353,0.000217628,0.0003944109,0.001898472,0.00003969995,0.0003879423,0.0003906831,0.001539529,0.03379383,0.01640249,0.7909757,0.1538273],"study_design_scores_gemma":[0.00002117287,0.00008531522,0.0003593607,0.0003257489,0.00001162874,0.0004260419,0.00005405306,0.0007383484,0.003003823,0.008018136,0.9869125,0.00004390566],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001640368,0.0360814,0.7617085,0.03506917,0.01785796,0.002729002,0.02239882,0.04001864,0.08249608],"genre_scores_gemma":[0.004327663,0.03237116,0.8345307,0.01236107,0.002222645,0.004909623,0.00834073,0.004833223,0.09610326],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.04726128,"threshold_uncertainty_score":0.1581047,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04483837717998766,"score_gpt":0.3862145781297184,"score_spread":0.3413762009497308,"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."}}