{"id":"W7098190136","doi":"","title":"EFFECTIVENESS OF COMPENSATION STRATEGIES IN CANADIAN TECHNOLOGY-INTENSIVE FIRMS","year":2013,"lang":"en","type":"article","venue":"","topic":"Diverse Scientific and Economic Studies","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Incentive; Staffing; Compensation (psychology); Perspective (graphical); Human resources; Executive compensation; Human resource management","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001709773,0.0002300865,0.000293714,0.001982788,0.002646964,0.001902806,0.0009104555,0.0005066405,0.001332656],"category_scores_gemma":[0.009173423,0.0002183095,0.0002288987,0.002812617,0.0008602369,0.0003898821,0.001018675,0.0005014715,0.0001060273],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.03134993,"about_ca_system_score_gemma":0.02805871,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.961246,"about_ca_topic_score_gemma":0.9814741,"domain_scores_codex":[0.9977438,0.0002386456,0.00009318176,0.0001719031,0.0009801392,0.000772284],"domain_scores_gemma":[0.989889,0.001290334,0.003705985,0.000282615,0.002403049,0.002429069],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000162129,0.0001521415,0.9745317,0.00003472387,0.0000302731,0.0000707494,0.002513391,0.0004102387,0.0005702589,0.0003497823,0.000442588,0.02073202],"study_design_scores_gemma":[0.000004057134,0.00002539501,0.998292,0.000007204941,0.000004415626,0.00001139529,0.001025756,0.0001430507,0.00006368208,0.00002121258,0.0003943075,0.000007627218],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9983315,0.0002063863,0.00002239028,0.0001136786,0.000001994355,0.00001000404,0.0001173125,0.000001854442,0.001194836],"genre_scores_gemma":[0.9992397,0.0001439013,0.00004737259,0.00003123392,0.000001721078,0.000002917646,0.0001345097,6.688077e-7,0.0003981142],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03875405,"threshold_uncertainty_score":0.2274607,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0200283460267961,"score_gpt":0.2001900501515091,"score_spread":0.180161704124713,"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."}}