{"id":"W7045511858","doi":"","title":"Auswertung von Häufigkeitsverteilungen und Korrelationen der Proteine Hdm2, P53, P63, P14ARF und P16INK4a im invasiven Harnblasenkarzinom an digitalisierten Tissue Mikroarrays","year":2013,"lang":"de","type":"dissertation","venue":"OPUS FAU (Kooperativer Bibliotheksverbund Berlin-Brandenburg (KOBV), on behalf of the Universitätsbibliothek Erlangen-Nürnberg)","topic":"Online Learning Methods and Innovations","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"p14arf; Bladder cancer; Tissue microarray; Cancer; Economic shortage; Microarray; Erythroblast; Carcinoma","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","bibliometrics","sts","scholarly_communication","open_science","research_integrity","insufficient_payload"],"consensus_categories":["metaepi_narrow","bibliometrics","research_integrity","insufficient_payload"],"category_scores_codex":[0.0027015,0.002888354,0.003134288,0.01531717,0.004891939,0.002728491,0.005536018,0.002742656,0.008777044],"category_scores_gemma":[0.0009601875,0.002504497,0.001400984,0.03008339,0.002230573,0.007473343,0.0008042724,0.003385318,0.001150814],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001343202,"about_ca_system_score_gemma":0.002883694,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01488887,"about_ca_topic_score_gemma":0.006346682,"domain_scores_codex":[0.9831267,0.00393965,0.002881275,0.003397048,0.004092294,0.002563049],"domain_scores_gemma":[0.986624,0.001495705,0.003558649,0.003416461,0.003570532,0.001334625],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.01167772,0.0231307,0.04852892,0.00363814,0.04466893,0.001209789,0.2095739,0.02308402,0.2430199,0.07904371,0.221683,0.09074119],"study_design_scores_gemma":[0.02127453,0.007960944,0.03785189,0.006931683,0.01740105,0.00008802016,0.04219511,0.005841638,0.06757922,0.003610898,0.7751546,0.01411044],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9027516,0.01167506,0.002268299,0.00831959,0.00912702,0.01367491,0.004127384,0.0008156809,0.04724049],"genre_scores_gemma":[0.6182051,0.009229401,0.01021087,0.002430875,0.005719069,0.0003645021,0.01238391,0.001541218,0.3399151],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5534715,"threshold_uncertainty_score":0.9998445,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02870850560885882,"score_gpt":0.3431312449016114,"score_spread":0.3144227392927526,"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."}}