{"id":"W7073709411","doi":"","title":"Pharmaceutical Bar Coding: Moving Forward in Canada","year":2009,"lang":"en","type":"article","venue":"Europe PMC (PubMed Central)","topic":"QR Code Applications and Technologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Bar (unit); Work (physics); Field (mathematics); Welding","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":[0.01489313,0.0008837736,0.00114322,0.007942363,0.005209393,0.009305739,0.004271969,0.006188349,0.04820898],"category_scores_gemma":[0.04812764,0.000688404,0.001644373,0.01164925,0.006118784,0.004376341,0.002677259,0.005917907,0.007490259],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.08480369,"about_ca_system_score_gemma":0.3909588,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9657756,"about_ca_topic_score_gemma":0.9577174,"domain_scores_codex":[0.9820729,0.001792317,0.001188122,0.001246482,0.01042792,0.003272104],"domain_scores_gemma":[0.8771713,0.01282736,0.004099164,0.002691627,0.08857567,0.01463498],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002751215,0.0001635296,0.006033825,0.001059339,0.00003373559,0.0002907073,0.0006942433,0.001141441,0.001247768,0.0825718,0.5910988,0.3153897],"study_design_scores_gemma":[0.00008436582,0.0001115093,0.02340968,0.001426887,0.00004648263,0.0001981579,0.001345175,0.002139737,0.001386564,0.009228603,0.9604461,0.0001767826],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.02191554,0.03957888,0.02656748,0.7015411,0.02168306,0.0007718956,0.01355334,0.00372297,0.1706657],"genre_scores_gemma":[0.2419309,0.07015706,0.1050335,0.1553003,0.005762272,0.0004735086,0.01201199,0.002253275,0.4070772],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9151963,"threshold_uncertainty_score":0.6152967,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02201711997683808,"score_gpt":0.2340089137457257,"score_spread":0.2119917937688877,"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."}}