{"id":"W870727982","doi":"10.33119/gn/101394","title":"Offset Transactions and Industrial Development","year":2007,"lang":"en","type":"article","venue":"Gospodarka Narodowa","topic":"Diverse Education and Engineering Focus","field":"Social Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lockheed Martin (Canada)","funders":"","keywords":"Offset (computer science); Computer science; Operating system","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":[0.0004536951,0.0002264208,0.0002319311,0.001585734,0.001366829,0.006637028,0.0003215858,0.0007195751,0.02373615],"category_scores_gemma":[0.001756469,0.0001186417,0.00009495093,0.003656174,0.003415454,0.003713006,0.002572222,0.001313189,0.001023202],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002976959,"about_ca_system_score_gemma":0.002457757,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00559939,"about_ca_topic_score_gemma":0.01000719,"domain_scores_codex":[0.9994848,0.0001030236,0.00002420008,0.0000732034,0.0001829025,0.0001318663],"domain_scores_gemma":[0.9993382,0.0001914891,0.0001276472,0.00004903427,0.0001655249,0.00012816],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.00004744598,0.00002608602,0.005222761,0.00005797435,0.000008107659,0.0001247243,0.001232019,0.000487151,0.0003479477,0.9405934,0.003924188,0.0479282],"study_design_scores_gemma":[0.00001818867,0.00006500208,0.03002826,0.0002210249,0.00001658126,0.0003329898,0.009374603,0.0009206473,0.0007105484,0.5627663,0.3955158,0.00003003899],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.2736904,0.02590464,0.004651198,0.01239888,0.000351826,0.0000309719,0.0003295374,0.00004214159,0.6826004],"genre_scores_gemma":[0.9070387,0.005827629,0.0007145363,0.0002719325,0.0001034407,0.0000162276,0.0001048755,0.00001988077,0.0859027],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02373615,"threshold_uncertainty_score":0.07940531,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04323200371019958,"score_gpt":0.2872847200211576,"score_spread":0.244052716310958,"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."}}