{"id":"W4242272065","doi":"10.1038/s41587-019-0213-0","title":"Second-quarter biotech job picture","year":2019,"lang":"en","type":"article","venue":"Nature Biotechnology","topic":"Biotechnology and Related Fields","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Quarter (Canadian coin); Biotechnology; Job creation; Business; Biology; Economics; Labour economics; 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":[0.0006123378,0.0003578494,0.000256725,0.0007956572,0.003199101,0.003855164,0.0006819866,0.00245683,0.1979258],"category_scores_gemma":[0.001092105,0.0001423675,0.0002214417,0.0006588729,0.0004044532,0.001581843,0.001541377,0.002627605,0.07267217],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001698226,"about_ca_system_score_gemma":0.003078504,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01370123,"about_ca_topic_score_gemma":0.03344794,"domain_scores_codex":[0.999476,0.0000243926,0.00000963146,0.00004331308,0.0002322357,0.0002144618],"domain_scores_gemma":[0.9986901,0.0000466579,0.00003165394,0.00002631718,0.0002703701,0.0009348773],"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":[0.00008718818,0.00004012628,0.0007300915,0.00003008577,0.000001034285,0.00008684809,0.00009837219,0.00003955183,0.0004496668,0.003374766,0.9811475,0.01391476],"study_design_scores_gemma":[0.00001841305,0.00003753042,0.00953741,0.00002757817,0.000001075915,0.00007400316,0.0009886752,0.0001062285,0.0001987943,0.0009060198,0.9880946,0.000009603074],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.02455223,0.001816452,0.0006676656,0.2135458,0.03122618,0.00009151795,0.008485583,0.0006430722,0.7189716],"genre_scores_gemma":[0.02412755,0.000478797,0.0001169889,0.01213507,0.001639355,0.00002835784,0.001565371,0.00009877483,0.9598095],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.1979258,"threshold_uncertainty_score":0.6621277,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.002464835075798419,"score_gpt":0.2244046874269481,"score_spread":0.2219398523511497,"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."}}