{"id":"W1985479839","doi":"10.1021/cb600461v","title":"Seeing Is Believing","year":2006,"lang":"en","type":"article","venue":"ACS Chemical Biology","topic":"Advanced Fluorescence Microscopy Techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; National Science Foundation","keywords":"Subcellular localization; Visualization; Fluorescence microscope; Computational biology; Microscopy; Computer science; Fluorescence; Chemistry; Artificial intelligence; Biology; Biochemistry; Medicine; Pathology; Physics; Cytoplasm","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":[0.001944965,0.0006658118,0.0003576773,0.0006367827,0.003895063,0.006810166,0.0008180049,0.003144075,0.0600109],"category_scores_gemma":[0.01376023,0.0002550786,0.0004189241,0.0003131286,0.01200582,0.007422686,0.004168233,0.006177499,0.02667629],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001416248,"about_ca_system_score_gemma":0.001157764,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002486595,"about_ca_topic_score_gemma":0.004011663,"domain_scores_codex":[0.9976807,0.0007926956,0.00004243689,0.0003263811,0.0009166418,0.0002411242],"domain_scores_gemma":[0.9947451,0.00149099,0.0003483229,0.0008148351,0.001248646,0.001352054],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00006445628,0.00002754145,0.001609127,0.0001212526,0.00003440731,0.0004459249,0.009644775,0.0001251341,0.001448821,0.1315235,0.7875013,0.06745373],"study_design_scores_gemma":[0.000006662596,0.00002124515,0.0004646498,0.00009751588,0.00001140589,0.0007300795,0.004366522,0.0001072978,0.0004104374,0.0489165,0.9448429,0.00002497005],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.01122198,0.009805196,0.02845845,0.3194944,0.01814266,0.00005065007,0.000532213,0.001815513,0.610479],"genre_scores_gemma":[0.4175354,0.01033582,0.0161729,0.1718008,0.006465878,0.0001061295,0.0008089569,0.001888283,0.3748858],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0600109,"threshold_uncertainty_score":0.2007565,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004909490162862366,"score_gpt":0.2673875374878833,"score_spread":0.2624780473250209,"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."}}