{"id":"W4280550581","doi":"10.1038/s41587-022-01313-2","title":"First-quarter biotech job picture","year":2022,"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); 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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0009389195,0.0004357589,0.0003291979,0.0008222701,0.003119808,0.004957494,0.0007877177,0.002882402,0.2596851],"category_scores_gemma":[0.001637654,0.0001842808,0.0002852396,0.0007204895,0.0004695659,0.002301848,0.001694504,0.003581621,0.1184692],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00166507,"about_ca_system_score_gemma":0.003874314,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008846632,"about_ca_topic_score_gemma":0.02267102,"domain_scores_codex":[0.9992836,0.00003813497,0.00001572531,0.00006249373,0.0003374995,0.0002626366],"domain_scores_gemma":[0.9976456,0.00007506265,0.00004690492,0.00004073161,0.0004391248,0.001752671],"domain_codex":null,"domain_gemma":"incentives","domain_candidate":"incentives","domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.00005366656,0.00003417447,0.0003805988,0.00002595675,0.000001009656,0.00004108085,0.00003495348,0.00002377711,0.0002136956,0.002260237,0.9845691,0.01236175],"study_design_scores_gemma":[0.00001852692,0.0000330779,0.004194735,0.00003753765,0.000001200229,0.00005345622,0.0004958279,0.00007258413,0.0001344407,0.001069924,0.9938796,0.00000909677],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.009585802,0.003273441,0.0007580991,0.2880954,0.05394914,0.00008535078,0.007618628,0.0007983591,0.6358359],"genre_scores_gemma":[0.01971113,0.001215586,0.0002107675,0.02188394,0.003482177,0.00003218199,0.001901798,0.0001805336,0.9513819],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9990611,"threshold_uncertainty_score":0.8687332,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008400085781457471,"score_gpt":0.2888434868058425,"score_spread":0.2804434010243851,"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."}}