{"id":"W3112370574","doi":"10.1093/insilicoplants/diaa014","title":"Researcher Profile: Przemysław Prusinkiewicz","year":2020,"lang":"en","type":"article","venue":"in silico Plants","topic":"Greenhouse Technology and Climate Control","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Library science; Engineering; Computer science","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":[0.0001429585,0.00008972377,0.0001408884,0.000008942687,0.00006323651,0.00001916601,0.0002982622,0.000147624,0.0008932435],"category_scores_gemma":[0.00009761699,0.00003427862,0.00002902291,0.0002529667,0.00005578846,0.00006655847,0.00008205874,0.000238234,0.0004689695],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001054704,"about_ca_system_score_gemma":0.000006220395,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001011994,"about_ca_topic_score_gemma":0.0005882854,"domain_scores_codex":[0.9991085,0.00005754108,0.0001444761,0.0002436083,0.0001414369,0.0003044324],"domain_scores_gemma":[0.9997271,0.0001023394,0.00003028804,0.0000416679,0.00001553292,0.00008303776],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0002094253,0.0001601888,0.3639331,0.00001784851,0.0000146753,0.000172525,0.0003030794,0.000001592867,0.4403594,0.0004934624,0.007461144,0.1868736],"study_design_scores_gemma":[0.0004326662,0.0002197112,0.958402,0.00002957044,0.000003244827,0.00001137244,0.0003780755,0.0003224502,0.009088449,0.0005257167,0.03036753,0.0002191881],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9884759,0.000170079,2.093884e-7,0.008454886,0.00002632551,0.0002340221,0.00005961726,0.0001713405,0.002407621],"genre_scores_gemma":[0.9987473,0.00004363258,0.00001339752,0.0009375786,0.00008035822,0.00002779028,0.00003186461,7.806874e-7,0.0001172353],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.594469,"threshold_uncertainty_score":0.978039,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0583031086574809,"score_gpt":0.2484574442512174,"score_spread":0.1901543355937365,"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."}}