{"id":"W4256421228","doi":"10.1242/bio.046136","title":"First person – Peter Szaraz","year":2019,"lang":"en","type":"article","venue":"Biology Open","topic":"Mesenchymal stem cell research","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Biology; Library science; Selection (genetic algorithm); Test (biology); Engineering ethics; Computer science; Artificial intelligence; Ecology; Engineering","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":[0.004518155,0.00111918,0.0008139058,0.001293208,0.004558562,0.005820023,0.0008831064,0.002610682,0.2382533],"category_scores_gemma":[0.02620046,0.0005585838,0.0003024848,0.0007712091,0.002148646,0.005354718,0.004695247,0.006092787,0.1508814],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002966248,"about_ca_system_score_gemma":0.005794228,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002077728,"about_ca_topic_score_gemma":0.002428173,"domain_scores_codex":[0.9930497,0.002050484,0.0002771553,0.001227085,0.002664668,0.0007308708],"domain_scores_gemma":[0.979178,0.003085997,0.001222247,0.001050496,0.007910703,0.007552593],"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":[0.00004191184,0.00002400562,0.0001436052,0.00008192617,0.000002703155,0.0002569928,0.002131215,0.00002556114,0.0005289473,0.004399749,0.970777,0.02158651],"study_design_scores_gemma":[0.000005805531,0.000008826128,0.0001516578,0.00007461566,9.134632e-7,0.0003650398,0.002278034,0.00003804241,0.0001349913,0.0009148224,0.9960144,0.00001290103],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"other","genre_scores_codex":[0.009405541,0.01385401,0.01674168,0.5319067,0.09229964,0.0006364568,0.002527751,0.003590096,0.3290381],"genre_scores_gemma":[0.05781569,0.003539884,0.003878432,0.09180372,0.006347681,0.0005772833,0.0004217911,0.001483721,0.8341318],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.2382533,"threshold_uncertainty_score":0.7970365,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09135770305562381,"score_gpt":0.3791869457260431,"score_spread":0.2878292426704193,"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."}}