{"id":"W130108282","doi":"10.1007/978-3-642-41687-3_3","title":"Analytic Hierarchy Process to Improve the Evaluation Process in R&D Management System","year":2013,"lang":"en","type":"book-chapter","venue":"Lecture notes in business information processing","topic":"Multi-Criteria Decision Making","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Institute on Governance","funders":"","keywords":"Analytic hierarchy process; Normalization (sociology); Promotion (chess); Process (computing); Selection (genetic algorithm); Management science; Electric power; Risk analysis (engineering); Computer science; Process management; Work (physics); Quality (philosophy); Operations research; Engineering; Power (physics); Business; Artificial intelligence; Political science","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":[],"category_scores_codex":[0.007401619,0.0008663117,0.00109268,0.004336663,0.0004101178,0.003005062,0.002143541,0.0006317094,0.0005666719],"category_scores_gemma":[0.00616734,0.0005834525,0.0001409074,0.003556978,0.0001478759,0.004010168,0.0004358561,0.000923803,0.001063321],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001017263,"about_ca_system_score_gemma":0.0006754673,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002369089,"about_ca_topic_score_gemma":0.0001577513,"domain_scores_codex":[0.9885678,0.0001751384,0.003693728,0.001098236,0.005744062,0.0007210808],"domain_scores_gemma":[0.9898711,0.0008740915,0.00230365,0.001432412,0.005371905,0.0001468351],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001001979,0.00001854855,0.0001019031,0.001417393,0.00001626645,0.000006690242,0.004970255,0.1690097,0.000004940404,0.0008504531,0.00008595692,0.8234177],"study_design_scores_gemma":[0.003159599,0.00005460332,0.004910308,0.01275251,0.0002490777,0.00008713298,0.002553915,0.7400476,0.0001157369,0.1969332,0.03642822,0.002708024],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01197209,0.001053286,0.8422112,0.003467711,0.002327617,0.01164035,0.00006624031,0.0003402586,0.1269212],"genre_scores_gemma":[0.9900032,0.00001633084,0.005460299,0.001323052,0.0002694057,0.0009452728,0.0001298314,0.00009574713,0.001756826],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9780312,"threshold_uncertainty_score":0.9997145,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09545646247321421,"score_gpt":0.3966426795963825,"score_spread":0.3011862171231683,"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."}}