{"id":"W3010645847","doi":"10.12927/hcpol.2020.26133","title":"Lessons from the International Experience with Biosimilar Implementation: An Application of the Diffusion of Innovations Model","year":2020,"lang":"en","type":"article","venue":"Healthcare policy","topic":"Biosimilars and Bioanalytical Methods","field":"Immunology and Microbiology","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary; University of Alberta","funders":"University of Alberta","keywords":"Biosimilar; Context (archaeology); Business; Knowledge management; Marketing; Risk analysis (engineering); Computer science; Medicine; Geography","routes":{"ca_aff":true,"ca_fund":true,"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":[0.00009375723,0.00007229888,0.0001161195,0.0000251111,0.0001247396,0.000003878989,0.0003591733,0.00007496467,0.00006324602],"category_scores_gemma":[0.00004102645,0.00003839735,0.00003361299,0.0003219521,0.0002136544,0.00004238679,0.00009733074,0.0001331132,0.000001234985],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002136738,"about_ca_system_score_gemma":0.0001892711,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003198016,"about_ca_topic_score_gemma":0.0005969738,"domain_scores_codex":[0.9992881,0.000112085,0.0002653936,0.0001617533,0.00006357024,0.000109071],"domain_scores_gemma":[0.9993232,0.00005801669,0.0001844766,0.0002562623,0.0001571805,0.00002080287],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002330992,0.0001844977,0.07476979,0.00003305286,0.0001183953,1.287457e-7,0.01534872,0.00005169855,0.6603233,0.1770982,0.002162338,0.06967673],"study_design_scores_gemma":[0.002426203,0.0006686609,0.3316266,0.00007627997,0.0001064349,0.000009194729,0.01400487,0.009312891,0.5960001,0.008711087,0.03666447,0.0003931443],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.536182,0.0001801422,0.01286449,0.4489605,0.00008442497,0.0004066015,0.001215028,0.00002035865,0.00008645303],"genre_scores_gemma":[0.9886307,0.00002952921,0.001262385,0.009903125,0.00005625285,0.00002326338,0.00007882246,0.000005374203,0.00001052023],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4524487,"threshold_uncertainty_score":0.4834464,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0855200036463094,"score_gpt":0.4178667872870737,"score_spread":0.3323467836407643,"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."}}