{"id":"W2056991188","doi":"10.7202/050411ar","title":"La productivité des intelligences","year":2005,"lang":"fr","type":"article","venue":"Relations industrielles","topic":"Competitive and Knowledge Intelligence","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Humanities; Political science; Philosophy","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0005431242,0.0002749296,0.0002059915,0.0003297434,0.0005358689,0.0003963721,0.0003148362,0.0003602234,0.007752483],"category_scores_gemma":[0.0009314632,0.0002890409,0.0001214429,0.00132449,0.0007732395,0.002138091,0.0001930652,0.0006958268,0.01151344],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001256432,"about_ca_system_score_gemma":0.0001446681,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002626728,"about_ca_topic_score_gemma":0.0004582107,"domain_scores_codex":[0.9984696,0.00006644399,0.0004263235,0.0004149135,0.0002113545,0.000411358],"domain_scores_gemma":[0.9986814,0.0003648565,0.0001836222,0.000290959,0.0004477895,0.00003138003],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000008197179,0.0003010551,0.03082807,0.00003158084,0.00005571444,0.000008827953,0.0005950167,0.0009127178,0.00001671702,0.1879482,0.02563197,0.7536619],"study_design_scores_gemma":[0.00008572923,0.00001283938,0.00217342,0.0005224381,0.0001063802,0.00001612397,0.001963245,0.002440689,0.0009828839,0.007756684,0.9836022,0.0003374105],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.1488343,0.09889415,0.006418881,0.02579322,0.002031726,0.0005162798,0.00001351034,0.0002250681,0.7172729],"genre_scores_gemma":[0.8670096,0.001141472,0.0007636305,0.0001380921,0.004218513,0.00002036529,0.00001481582,0.0000319133,0.1266616],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9579702,"threshold_uncertainty_score":0.9999562,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04050722601103664,"score_gpt":0.2621860274404719,"score_spread":0.2216788014294353,"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."}}