{"id":"W1603068593","doi":"10.1111/caim.12014","title":"Commercial, Societal and Administrative Benefits from the Analysis and Clarification of Definitions: The Case of Nanomaterials","year":2013,"lang":"en","type":"article","venue":"Creativity and Innovation Management","topic":"Sustainable Supply Chain Management","field":"Business, Management and Accounting","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"Health Canada","keywords":"CLARITY; Taxonomy (biology); Management science; Risk analysis (engineering); Computer science; Knowledge management; Business; Data science; Economics; Ecology; Chemistry","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0007693762,0.0001307554,0.0002127204,0.0003016294,0.0003328692,0.0002712201,0.0001009748,0.00004051904,0.0001140389],"category_scores_gemma":[0.00008970979,0.00008886291,0.00003045982,0.001551971,0.0002957198,0.0006082286,0.0002513754,0.00005322299,0.00000191902],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001150452,"about_ca_system_score_gemma":0.000005431175,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002407483,"about_ca_topic_score_gemma":0.0001869078,"domain_scores_codex":[0.9991043,0.00005439956,0.0003887354,0.0002166833,0.0001254777,0.0001104297],"domain_scores_gemma":[0.9987995,0.0002250609,0.000439272,0.0002505806,0.0002801841,0.000005405777],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.00002215812,0.00009758333,0.03403172,0.0002969487,0.0007187527,0.000004736289,0.0005395493,0.00002388826,0.0001976081,0.9132579,0.001274115,0.04953505],"study_design_scores_gemma":[0.000569743,0.00002441242,0.9336775,0.0000428365,0.001200575,0.000002181002,0.02155987,0.002055787,0.0002359908,0.03810038,0.002340724,0.0001900052],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9910265,0.0001521541,0.001628133,0.003504619,0.00002920655,0.00080751,0.00002616484,0.0000152394,0.002810465],"genre_scores_gemma":[0.9983222,0.0001763598,0.0004475762,0.0007005456,0.00005505542,0.0001183597,0.0001096875,0.000006651196,0.0000635936],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8996457,"threshold_uncertainty_score":0.3639411,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06542453145823655,"score_gpt":0.2712660801387728,"score_spread":0.2058415486805362,"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."}}