{"id":"W2121390844","doi":"10.12948/issn14531305/18.3.2014.09","title":"Algorithms for Analyzing and Forecasting in a Pharmaceutical Company","year":2014,"lang":"en","type":"article","venue":"Informatica Economica","topic":"Forecasting Techniques and Applications","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Cybernet Systems Corporation (Canada)","funders":"","keywords":"Code (set theory); Computer science; Order (exchange); Class (philosophy); Principal (computer security); Operations research; Data mining; Business; Artificial intelligence; Engineering; Computer security; Finance; Programming language","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":[],"consensus_categories":[],"category_scores_codex":[0.002641808,0.0001021661,0.0002810629,0.0002243457,0.0001220101,0.000234247,0.0003397751,0.0000510152,0.0000461719],"category_scores_gemma":[0.001278985,0.00008580591,0.0000626779,0.0001763499,0.00009190061,0.0003610108,0.0001272648,0.0001033627,0.00005440653],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003141145,"about_ca_system_score_gemma":0.00001817033,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000953462,"about_ca_topic_score_gemma":0.00001434547,"domain_scores_codex":[0.9984821,0.00002604174,0.0009298352,0.0002026,0.0001046702,0.0002547544],"domain_scores_gemma":[0.9973913,0.001949274,0.0002260774,0.000266793,0.00005929044,0.0001072164],"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":[0.00003200609,0.00003561935,0.01161237,0.00003451268,0.0000115568,1.65557e-7,0.0006988634,0.0005844742,0.00005682836,0.08516166,0.002926743,0.8988452],"study_design_scores_gemma":[0.0004018651,0.00003222569,0.002220031,0.0000151579,0.000003850129,0.000008297962,0.0001010657,0.8930185,0.0001372918,0.04765281,0.05628979,0.0001191281],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7601043,0.00001783424,0.2161992,0.001673916,0.00007503881,0.0006465368,0.00002893949,0.00009653058,0.02115777],"genre_scores_gemma":[0.9035835,0.000003202213,0.09592733,0.000300422,0.00004549745,0.00008437907,0.000003708039,0.000006874558,0.00004510288],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.898726,"threshold_uncertainty_score":0.3499064,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.244677495996747,"score_gpt":0.4161193905555252,"score_spread":0.1714418945587781,"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."}}