{"id":"W4239575817","doi":"10.1038/s41587-019-0022-5","title":"Fourth-quarter biotech job picture","year":2019,"lang":"en","type":"article","venue":"Nature Biotechnology","topic":"Science, Research, and Medicine","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Quarter (Canadian coin); Snapshot (computer storage); Job creation; Biotechnology; Business; Biology; Labour economics; Economics; Computer science; Geography","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":[0.0009508092,0.0004161548,0.0002848271,0.0008113261,0.002977628,0.004364955,0.0008014281,0.002855886,0.1759535],"category_scores_gemma":[0.001396924,0.0001645036,0.0002794613,0.0006394833,0.0005146457,0.001696343,0.001712568,0.003092919,0.07448182],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001793834,"about_ca_system_score_gemma":0.003973862,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01132269,"about_ca_topic_score_gemma":0.02754288,"domain_scores_codex":[0.9993458,0.00003481626,0.00001365366,0.00005037702,0.0003033095,0.0002519401],"domain_scores_gemma":[0.9981824,0.00005821046,0.00004045706,0.00003850002,0.0003498491,0.00133057],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.00006589518,0.00003521864,0.0004981751,0.00002330972,0.000001043891,0.00004446695,0.00004195265,0.00003756267,0.0002731024,0.002721279,0.9832139,0.01304415],"study_design_scores_gemma":[0.00001960688,0.00003699066,0.005777962,0.00003126348,0.000001307445,0.00004506469,0.0005219069,0.0001102707,0.0001675089,0.001147514,0.9921313,0.000009353069],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.01699876,0.002729073,0.0008554574,0.3380114,0.05368846,0.00008567706,0.007282387,0.0008182075,0.5795305],"genre_scores_gemma":[0.02211133,0.000798561,0.0001886083,0.01709381,0.002669545,0.00003180598,0.001541955,0.0001139905,0.9554504],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.1759535,"threshold_uncertainty_score":0.588623,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006736956872910365,"score_gpt":0.29166496860038,"score_spread":0.2849280117274697,"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."}}