{"id":"W2266671328","doi":"","title":"The sustainable fibres of generative expectation management: The “building with hemp” case study.","year":2012,"lang":"en","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Innovation and Knowledge Management","field":"Business, Management and Accounting","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Montréal InVivo","funders":"","keywords":"Generative grammar; Business; Computer science; Artificial intelligence","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004412308,0.0003147409,0.0001783028,0.0006116434,0.003917348,0.004436051,0.001570849,0.002704966,0.00853112],"category_scores_gemma":[0.008375807,0.0002571998,0.0004403298,0.001002102,0.005394949,0.004190721,0.004892117,0.001783732,0.0009936151],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002673708,"about_ca_system_score_gemma":0.003963358,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005843619,"about_ca_topic_score_gemma":0.01353051,"domain_scores_codex":[0.9945649,0.004285393,0.00005468184,0.000158581,0.0004784297,0.0004580181],"domain_scores_gemma":[0.9932045,0.005039251,0.0002430671,0.0007635778,0.0002215949,0.0005279793],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"qualitative","study_design_scores_codex":[0.0002412769,0.0009579664,0.01195851,0.0003534769,0.00005595655,0.0109931,0.1410253,0.01164152,0.002921201,0.650317,0.01891977,0.1506149],"study_design_scores_gemma":[0.0001058375,0.0005664921,0.01206546,0.0006266631,0.00007739415,0.005377901,0.2248228,0.03221677,0.008544654,0.4366657,0.2787963,0.0001340994],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5322949,0.0005416198,0.08234875,0.0110719,0.00008354525,0.0003972546,0.0002251351,0.0002735597,0.3727632],"genre_scores_gemma":[0.9703431,0.000188618,0.01838638,0.0003159327,0.000007180367,0.00009006356,0.0000773939,0.00005581225,0.01053553],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00853112,"threshold_uncertainty_score":0.02853948,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01532936089318651,"score_gpt":0.2333651511867354,"score_spread":0.2180357902935489,"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."}}