{"id":"W4406147632","doi":"10.1017/s0266462324003854","title":"PD153 Horizon Scanning Analysis Of The Obesity Medicines Pipeline","year":2024,"lang":"en","type":"article","venue":"International Journal of Technology Assessment in Health Care","topic":"Natural Products and Biological Research","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Pipeline (software); Horizon; Medicine; Obesity; Business; Computer science; Internal medicine; Mathematics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008793447,0.00007694867,0.0003712607,0.00133704,0.0000306205,0.00001062949,0.0003892891,0.0001192987,0.00008914887],"category_scores_gemma":[0.0005970424,0.00003940327,0.0001734559,0.00139174,0.0001329156,0.0000491442,0.0001274772,0.0009683768,5.47829e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004706268,"about_ca_system_score_gemma":0.0005810612,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006521365,"about_ca_topic_score_gemma":0.00003323759,"domain_scores_codex":[0.9983373,0.0000629542,0.0006573919,0.0001456398,0.0006483262,0.0001484293],"domain_scores_gemma":[0.9985862,0.0001204166,0.0002599909,0.0001378488,0.0008464743,0.00004910609],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002928048,0.0003311747,0.7001618,0.0005315776,0.00193558,0.0005125238,0.0003133717,0.0002180899,0.006164519,0.01799658,0.003103084,0.2684388],"study_design_scores_gemma":[0.001749232,0.003351716,0.9431175,0.004709848,0.0006363037,0.0005052494,0.007733175,0.003672156,0.005040506,0.003151146,0.02614231,0.0001908577],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8103374,0.01327216,0.000207156,0.1747462,0.00100003,0.0001659897,0.00001573301,0.00001888521,0.0002364115],"genre_scores_gemma":[0.997597,0.0009736017,0.000782227,0.0003813527,0.0001904895,0.000001594403,0.00001162198,0.000004111491,0.00005795814],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.268248,"threshold_uncertainty_score":0.4207169,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02402608129375037,"score_gpt":0.445625740955133,"score_spread":0.4215996596613826,"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."}}