{"id":"W4241614837","doi":"10.1504/ijor.2016.078465","title":"Relative efficiency of hardware retail stores chains in Canada","year":2016,"lang":"en","type":"article","venue":"International Journal of Operational Research","topic":"Efficiency Analysis Using DEA","field":"Decision Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Laurentian University","funders":"","keywords":"Business; Private sector; Efficiency; Supply chain; Data envelopment analysis; Industrial organization; Finance; Economics; Marketing; Economic growth","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.001251188,0.0003604589,0.0005181753,0.002940452,0.001582298,0.004357324,0.0008106719,0.0003360014,0.00264961],"category_scores_gemma":[0.005587813,0.0003955354,0.0006377912,0.006462385,0.001363725,0.001078425,0.00139964,0.0005456075,0.000227649],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.04985064,"about_ca_system_score_gemma":0.02185851,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9720994,"about_ca_topic_score_gemma":0.9782706,"domain_scores_codex":[0.9982424,0.0001136023,0.00006867371,0.0001900587,0.000685586,0.0006997427],"domain_scores_gemma":[0.9969729,0.0004858039,0.0003796855,0.0001679535,0.001726266,0.0002673157],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0008529888,0.0001783319,0.5399036,0.0002429085,0.00033612,0.000756788,0.002423228,0.3137654,0.003521531,0.05829562,0.004958356,0.07476519],"study_design_scores_gemma":[0.00004615689,0.00009931208,0.7116344,0.0001288091,0.0001184232,0.0001670352,0.009634874,0.2502185,0.004310507,0.007085284,0.01640318,0.0001535271],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9842482,0.0004182414,0.001620227,0.0001923865,0.000003772479,0.00003454156,0.001445568,0.00002764252,0.01200944],"genre_scores_gemma":[0.9958375,0.0002409631,0.0008979415,0.00001191233,9.162479e-7,0.000006474591,0.0007654984,0.00001119492,0.002227595],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04985064,"threshold_uncertainty_score":0.3616934,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1879531801881098,"score_gpt":0.4688070999832162,"score_spread":0.2808539197951064,"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."}}