{"id":"W1981036232","doi":"10.1016/j.ifset.2009.10.007","title":"Possibilities for an in vitro meat production system","year":2009,"lang":"en","type":"article","venue":"Innovative Food Science & Emerging Technologies","topic":"Agriculture Sustainability and Environmental Impact","field":"Environmental Science","cited_by":336,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"Universiteit Utrecht; University of Georgia; Medical University of South Carolina","keywords":"Scope (computer science); Meat packing industry; Production (economics); Biotechnology; Business; Food science; Biochemical engineering; Biology; Computer science; Engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009258954,0.0002083682,0.0001957117,0.0002491918,0.0004315074,0.0000685831,0.0006977692,0.00009920173,0.000004797108],"category_scores_gemma":[0.0005187306,0.0001571094,0.00003104023,0.003457771,0.001600554,0.001679333,0.0002076512,0.0001986516,0.000006641992],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001095834,"about_ca_system_score_gemma":0.0000315149,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006420229,"about_ca_topic_score_gemma":0.00003016621,"domain_scores_codex":[0.9979303,0.00002545251,0.000306814,0.0007259377,0.0004038215,0.0006076372],"domain_scores_gemma":[0.9993279,0.00001890735,0.0001176172,0.0004487831,0.00005132413,0.00003546945],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00007911455,0.0002101428,0.004575922,0.00002136139,0.000003379718,0.000001623307,0.002331593,0.001399164,0.9313614,0.007060466,0.000167249,0.05278856],"study_design_scores_gemma":[0.0002100864,0.001248656,0.04777199,0.00002999169,0.000003674817,0.00001281523,0.08930954,0.0004722918,0.841629,0.0185833,0.0003576065,0.0003710081],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9946488,0.00002519365,0.0006059448,0.002159698,0.0001220238,0.000824061,0.00000645313,0.0006293538,0.0009784505],"genre_scores_gemma":[0.9946728,0.000001834406,0.005138729,0.00003921028,0.00001602593,0.00007425044,0.000003917843,0.000005908342,0.00004734156],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08973239,"threshold_uncertainty_score":0.6406734,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01854470344879887,"score_gpt":0.2712124517470622,"score_spread":0.2526677482982633,"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."}}