{"id":"W7100637693","doi":"","title":"Canadian high technology firms ’ key performance","year":2007,"lang":"en","type":"article","venue":"","topic":"Forensic Fingerprint Detection Methods","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Information technology; Strategic management; Strategic planning; Technology management; Human resource management; Investment (military); Population; Strategic human resource planning; Key (lock)","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":[0.0009492185,0.0002118306,0.000139297,0.003143683,0.004655565,0.002370923,0.0005753984,0.0002358211,0.006963897],"category_scores_gemma":[0.004140042,0.0001005971,0.0001157433,0.006653452,0.0007401187,0.0005823133,0.0009342115,0.0003416437,0.0004988651],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.04111902,"about_ca_system_score_gemma":0.02636378,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9826916,"about_ca_topic_score_gemma":0.9933888,"domain_scores_codex":[0.998782,0.00008968147,0.00002707197,0.0001096422,0.0006815022,0.0003101901],"domain_scores_gemma":[0.9958556,0.0004458583,0.0004116895,0.0001053852,0.002442461,0.0007389536],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002457369,0.0001279093,0.6897205,0.0003312609,0.000055163,0.0006718876,0.04455515,0.00159961,0.003440969,0.02366371,0.03266729,0.2029209],"study_design_scores_gemma":[0.000006223913,0.00004294152,0.9155889,0.00005958258,0.00001883611,0.0001034527,0.03715632,0.0007014865,0.001244618,0.0004791855,0.04453687,0.0000615005],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8889126,0.0005367238,0.0004849335,0.0008055326,0.00001498661,0.00006546133,0.003208643,0.00002766148,0.1059434],"genre_scores_gemma":[0.9874643,0.0002944424,0.0004388826,0.00004910767,0.000002331836,0.00001454871,0.0007001979,0.000004525005,0.01103149],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04111902,"threshold_uncertainty_score":0.2983408,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01267685344111408,"score_gpt":0.2974630692231084,"score_spread":0.2847862157819944,"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."}}