{"id":"W7037149761","doi":"","title":"The downs and ups of mark-ups","year":2023,"lang":"en","type":"other","venue":"Econstor (Econstor)","topic":"Library Collection Development and Digital Resources","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Inflation (cosmology); Norwegian; Renting; Sample (material); Capital (architecture); Percentage point; Quarter (Canadian coin); Aggregate data","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":[],"consensus_categories":[],"category_scores_codex":[0.0002450961,0.0003175529,0.0003963859,0.0004263956,0.0002189806,0.0003761023,0.0009470951,0.0002148282,0.0005662373],"category_scores_gemma":[0.00009983294,0.0002433555,0.0001328366,0.0004856204,0.0003961548,0.0004043781,0.0004884824,0.0001953688,0.0004128815],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005058058,"about_ca_system_score_gemma":0.0003800271,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003867255,"about_ca_topic_score_gemma":0.0002451851,"domain_scores_codex":[0.9983574,0.00005993687,0.0004109883,0.0005315454,0.0002803525,0.0003598447],"domain_scores_gemma":[0.9983032,0.0005211398,0.0003626114,0.0006278854,0.00002926591,0.000155858],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000005361382,0.00001805483,0.09151742,0.00003218242,0.0001295907,0.00001600769,0.0001419315,3.307279e-7,0.000001470722,0.009512112,0.889673,0.008952536],"study_design_scores_gemma":[0.0002723211,0.00003838808,0.01564749,0.0001058828,0.000009008309,0.00003127257,0.00003982711,0.00005851778,0.00002688486,0.0007252232,0.9827023,0.0003429416],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.004418858,0.002692444,0.0002582029,0.0004637508,0.002630602,0.000328662,0.00003915859,0.0008353712,0.9883329],"genre_scores_gemma":[0.002605551,0.000863651,0.0009359192,0.0001407522,0.0002432179,0.00003913221,0.000003665536,0.0002182708,0.9949498],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.09302924,"threshold_uncertainty_score":0.9923751,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009856888228082818,"score_gpt":0.2006599898836694,"score_spread":0.1908031016555866,"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."}}