{"id":"W2157676453","doi":"10.1017/s1431927602107227","title":"Microscope or MACROscope – Which System Provides a Better Scope on Image Analysis??","year":2002,"lang":"en","type":"article","venue":"Microscopy and Microanalysis","topic":"Electron and X-Ray Spectroscopy Techniques","field":"Materials Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Princess Margaret Cancer Centre; Ontario Institute for Cancer Research","funders":"","keywords":"Scope (computer science); Microscope; Materials science; Image (mathematics); Computer science; Computer vision; Optics; Physics","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0008376741,0.0008473896,0.001494038,0.001029266,0.0008351429,0.001156847,0.000838905,0.0003188015,0.003673887],"category_scores_gemma":[0.00007401106,0.0006594288,0.0004629298,0.003104986,0.000401032,0.0005235688,0.0002447247,0.0004804213,0.001006735],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003191634,"about_ca_system_score_gemma":0.0000740296,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004536274,"about_ca_topic_score_gemma":0.0008299247,"domain_scores_codex":[0.9950236,0.0003506433,0.001038965,0.001738037,0.0005018231,0.001346927],"domain_scores_gemma":[0.9974539,0.0001475975,0.0004508444,0.001311033,0.0002833003,0.0003532771],"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":[0.0002422451,0.0002590517,0.001142308,0.0001743883,0.0005636425,0.00005432572,0.0003426452,0.000005695242,0.9871537,0.0001176314,0.00938335,0.0005609811],"study_design_scores_gemma":[0.0007002064,0.0005208178,0.000281312,0.0001731522,0.002052554,0.00004686924,0.0001909912,0.0005962204,0.9880161,0.00001842258,0.006583301,0.0008200599],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.983355,0.003569748,0.006098032,0.0009326456,0.0002021042,0.0008224009,0.0002460338,0.0008204036,0.003953557],"genre_scores_gemma":[0.9509755,0.0009949793,0.03970448,0.001609894,0.0001812573,0.0001736208,0.0000725854,0.0001234526,0.006164169],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03360645,"threshold_uncertainty_score":0.9998801,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01063255712389883,"score_gpt":0.2695034017447056,"score_spread":0.2588708446208068,"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."}}