{"id":"W2363945862","doi":"","title":"The Design of Intelligent Slide Stainers for Medical Specimen","year":2004,"lang":"en","type":"article","venue":"Zhongguo yixue wulixue zazhi","topic":"Simulation and Modeling Applications","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"L'Alliance Boviteq","funders":"","keywords":"Microcomputer; Computer science; Computer graphics (images); Computer vision; Artificial intelligence; Engineering drawing; Telecommunications; 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":[0.0004605884,0.0006176337,0.0004316365,0.0003701511,0.0005310749,0.0005741097,0.001436527,0.0008121433,0.001764687],"category_scores_gemma":[0.0007310089,0.0005101597,0.0003940612,0.0001783019,0.000403866,0.0007647769,0.0005283968,0.000429591,0.0008486378],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000372256,"about_ca_system_score_gemma":0.0006143405,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004968054,"about_ca_topic_score_gemma":0.000841175,"domain_scores_codex":[0.999566,0.00005591133,0.00002218267,0.0000849057,0.0002383238,0.00003264596],"domain_scores_gemma":[0.9996161,0.00008491288,0.00005772305,0.00004606922,0.0001572971,0.00003786299],"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":[0.0002854608,0.0001040992,0.003344462,0.0007994311,0.000135401,0.0007606616,0.0006035971,0.06900504,0.6119304,0.02488763,0.007704598,0.2804393],"study_design_scores_gemma":[0.00007979564,0.0009681252,0.002923574,0.00007892943,0.0001929432,0.001780925,0.0001790893,0.5597128,0.3200963,0.004262941,0.1095799,0.0001447458],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01038778,0.000254056,0.9848711,0.0001303636,0.0001584716,0.0001213765,0.0000285203,0.001074603,0.002973781],"genre_scores_gemma":[0.1976712,0.0005543412,0.7936239,0.000162516,0.00009479465,0.0002942741,0.00008944642,0.0001316108,0.007378025],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001764687,"threshold_uncertainty_score":0.005903482,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02555474757570641,"score_gpt":0.2735938067155071,"score_spread":0.2480390591398007,"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."}}