{"id":"W2160676227","doi":"10.1111/1911-3838.12021","title":"A Balanced Scorecard for Maple Leaf Consulting","year":2013,"lang":"en","type":"article","venue":"Accounting Perspectives","topic":"Botanical Studies and Applications","field":"Agricultural and Biological Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Maple; Balanced scorecard; Business; Botany; Biology; Marketing","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009068941,0.00009081125,0.0001236735,0.000001391198,0.0005311582,0.0001100344,0.0001475348,0.00004018224,0.0003082354],"category_scores_gemma":[0.0001884696,0.00003560018,0.00008062089,0.0001584907,0.00006228463,0.0001154352,0.00005853081,0.0000597827,0.00008063069],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003051796,"about_ca_system_score_gemma":0.000001520214,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007198044,"about_ca_topic_score_gemma":0.0002204846,"domain_scores_codex":[0.9992802,0.000008910273,0.0001228334,0.0002630364,0.00007793564,0.0002471019],"domain_scores_gemma":[0.9993399,0.0003320035,0.00006621626,0.00004084948,0.0001849545,0.00003606128],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.00002713294,0.0002712663,0.05441981,0.00001968446,0.0001040461,3.318636e-7,0.001890434,0.000004690914,0.4488383,0.01097157,0.015499,0.4679537],"study_design_scores_gemma":[0.0005338255,0.0001875886,0.8266078,0.00004371888,0.00003100334,0.000003608724,0.04187537,0.0006978982,0.001820066,0.006863113,0.120717,0.0006189496],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9879506,0.0002472249,0.00003923631,0.009966665,0.00003987844,0.0004412455,0.00001781819,0.0001000519,0.001197302],"genre_scores_gemma":[0.9980454,0.00003724631,0.0008874597,0.0002344194,0.0003665535,0.0002549273,0.000007110005,0.000001079464,0.0001658001],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.772188,"threshold_uncertainty_score":0.4085293,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01892973172835918,"score_gpt":0.2345304113476296,"score_spread":0.2156006796192704,"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."}}