{"id":"W7132395261","doi":"","title":"AstraZeneca (China): Leveraging Offline Doctor-Patient Relationships in Online Healthcare Service Platform","year":2022,"lang":"en","type":"other","venue":"CEIBS Institutional Repository","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Centre Casa","funders":"","keywords":"Competitor analysis; Pharmaceutical marketing; Pharmaceutical industry; The Internet; Online and offline; Medical prescription; Service (business); Procurement; Competitive advantage","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"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":[0.002552334,0.000288041,0.0001419963,0.0007329289,0.002085132,0.00331748,0.0006205062,0.0009196965,0.007166682],"category_scores_gemma":[0.003096313,0.0001668587,0.0003636353,0.001086632,0.001058493,0.003315916,0.003418158,0.001185616,0.001593354],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0012318,"about_ca_system_score_gemma":0.006277504,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004838631,"about_ca_topic_score_gemma":0.009116578,"domain_scores_codex":[0.9982481,0.0009248948,0.00005528153,0.000140799,0.0003421992,0.0002886714],"domain_scores_gemma":[0.9969688,0.0004781366,0.0002022769,0.0002368592,0.000326119,0.001787848],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003982839,0.001002217,0.05044071,0.0006438122,0.0000749106,0.002439908,0.01505807,0.0008863747,0.01012139,0.03445968,0.1263872,0.7580875],"study_design_scores_gemma":[0.0004436808,0.00253281,0.07486948,0.0007225894,0.000254416,0.003514373,0.02258072,0.01771507,0.009289791,0.0204968,0.8472924,0.0002879659],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"other","genre_scores_codex":[0.5805973,0.008422048,0.02454158,0.09940817,0.001412843,0.0009333958,0.0005044838,0.002897285,0.2812829],"genre_scores_gemma":[0.9285526,0.004111053,0.01703628,0.008295268,0.0004436014,0.00020734,0.0003846383,0.0001300745,0.04083911],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.007166682,"threshold_uncertainty_score":0.02397496,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04705211111879867,"score_gpt":0.2727900456347739,"score_spread":0.2257379345159752,"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."}}