{"id":"W3041753411","doi":"10.5539/mas.v14n8p35","title":"Positivities of Globalization in the Domain of Developing the Human Resources","year":2020,"lang":"en","type":"article","venue":"Modern Applied Science","topic":"Gender, Education, and Development Issues","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Globalization; Correctness; Human resources; Domain (mathematical analysis); Meaning (existential); Clearing; Dimension (graph theory); Business; Political science; Psychology; Computer science; Mathematics; Law","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001656655,0.00005140476,0.00008202699,0.00004525259,0.0007112375,0.00006605904,0.0006845199,0.00002089025,0.000008449349],"category_scores_gemma":[0.00005320421,0.00003368407,0.00001314607,0.0009666116,0.0009484247,0.0001135834,0.00003675915,0.00004007015,9.791171e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003907034,"about_ca_system_score_gemma":0.0004170291,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005363807,"about_ca_topic_score_gemma":0.0006245737,"domain_scores_codex":[0.9987898,0.00008979858,0.0001798381,0.000152999,0.0006212651,0.0001663245],"domain_scores_gemma":[0.9996201,0.00007718815,0.0001032724,0.0001074962,0.0000658194,0.0000260885],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.00000220479,0.00001228826,0.004857727,0.000008721354,0.000001185019,6.497655e-8,0.7164202,0.00004310804,0.01110363,0.2671117,0.00006975704,0.0003694692],"study_design_scores_gemma":[0.0002452559,0.00002480768,0.1641176,0.00004330172,0.000007986131,4.147467e-7,0.6386537,0.0004786518,0.01407586,0.172559,0.009542024,0.0002513905],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9166506,0.00006858488,0.01194188,0.004909259,0.00003356214,0.0002436761,0.000001018289,0.00001352435,0.06613789],"genre_scores_gemma":[0.9985806,0.00001652317,0.0009355639,0.000384484,0.00003309044,0.000008215226,8.007352e-7,0.000001969818,0.00003873613],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1592599,"threshold_uncertainty_score":0.5470336,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04350304143614106,"score_gpt":0.3138248082445719,"score_spread":0.2703217668084309,"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."}}