{"id":"W6960448319","doi":"10.1371/journal.pone.0180375.g004","title":"Publication rates and geographical distribution of 3D bioprinting patents.","year":2017,"lang":"en","type":"other","venue":"Figshare","topic":"Soybean genetics and cultivation","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Distribution (mathematics); 3D bioprinting; Patent analysis","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":["bibliometrics"],"consensus_categories":[],"category_scores_codex":[0.001934546,0.0003643548,0.0003112051,0.01897277,0.0002754918,0.001762685,0.0004673383,0.0003238014,0.01881388],"category_scores_gemma":[0.009273891,0.0001507266,0.0007140808,0.01688525,0.000290131,0.001144412,0.0006402825,0.0005155556,0.006464871],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005887106,"about_ca_system_score_gemma":0.0007326259,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00519474,"about_ca_topic_score_gemma":0.006924095,"domain_scores_codex":[0.9983625,0.0001874355,0.0002651897,0.000428284,0.000523653,0.0002330023],"domain_scores_gemma":[0.987253,0.004043895,0.004446847,0.0005413449,0.002758804,0.0009561644],"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":[0.001080945,0.0001066696,0.2378899,0.003311047,0.0007382156,0.0008381488,0.0009844551,0.00231047,0.006904908,0.01382344,0.3692681,0.3627437],"study_design_scores_gemma":[0.00009096789,0.0002266702,0.6310984,0.0006090513,0.0002617368,0.001218584,0.0008958409,0.001987736,0.002802772,0.001627239,0.3590929,0.00008816759],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.3259731,0.04048835,0.002166369,0.002032904,0.001101373,0.0001625181,0.5061248,0.00223902,0.1197115],"genre_scores_gemma":[0.6295809,0.0235138,0.004454007,0.0007350433,0.000527885,0.0002731942,0.2683195,0.0005488699,0.07204682],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.9810272,"threshold_uncertainty_score":0.06293869,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0422719359889102,"score_gpt":0.2415073951203116,"score_spread":0.1992354591314014,"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."}}