{"meta":{"query_hash":"b3a0ba82ed1b","filters":{"venue":"Recherche d’information document et web sémantique"},"cohort_total":1,"direct_labels_cover":0,"predictions_cover":1,"exported":1,"export_cap":100000,"truncated":false,"label_status":"direct model label, unvalidated","prediction_status":"machine_predicted_unvalidated (Codex and Gemma teacher distillation)","score_status":"score_only:v0-immature-baseline","snapshot":{"source":"OpenAlex, pinned release, all 482 partitions","release":"2026-06-24","frame_built":"2026-07-12"},"permalink":"https://metacan.xera.ac/q/b3a0ba82ed1b","api":"https://metacan.xera.ac/api/v1/cohort?venue=Recherche+d%E2%80%99information+document+et+web+s%C3%A9mantique"},"results":[{"id":"W2782126927","doi":"10.21494/iste.op.2018.0206","title":"Les espaces sémantiques de mots-clés : une méthode d’indexation automatique de documents par assignation de mots-clés","year":2017,"lang":"fr","type":"article","venue":"Recherche d’information document et web sémantique","topic":"Natural Language Processing Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"Indexation; Humanities; Art; Economics","score_opus":0.08990668803295894,"score_gpt":0.3943007640468393,"score_spread":0.30439407601388035,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2782126927","genre_codex":"methods","genre_gemma":"methods","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"methods","genre_consensus":"methods","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00871557,0.0004261053,0.9775613,0.0005219731,0.00017733329,0.00014852644,0.0010430238,0.007888484,0.0035177923],"genre_scores_gemma":[0.072550684,0.00040737298,0.9088482,0.00021495871,0.00011205909,0.00026333274,0.0017769121,0.0022050852,0.013621402],"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","domain_scores_codex":[0.99586064,0.00087369146,0.0004300261,0.0009901316,0.001645093,0.00020051753],"domain_scores_gemma":[0.9931017,0.0027387391,0.000437387,0.0015797426,0.0019387935,0.00020354007],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0037163906,0.0013954531,0.0012075262,0.0044815335,0.0018950809,0.006227604,0.0022210819,0.0016159005,0.009088944],"category_scores_gemma":[0.013444062,0.000988668,0.0017754455,0.005502191,0.0020186421,0.005091418,0.0026340291,0.0023806193,0.0058897533],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00058926735,0.00017909847,0.0031927254,0.0007869165,0.0001804863,0.00024940146,0.0025332354,0.010434729,0.041950546,0.055702277,0.024759304,0.85944206],"study_design_scores_gemma":[0.00025011456,0.00023930236,0.007387101,0.00036546992,0.00028814824,0.0014489894,0.0017279629,0.4824096,0.17142585,0.10315497,0.2308664,0.00043608528],"about_ca_topic_score_codex":0.014065703,"about_ca_topic_score_gemma":0.015622443,"teacher_disagreement_score":0.014065703,"about_ca_system_score_codex":0.0017016935,"about_ca_system_score_gemma":0.0027522314,"threshold_uncertainty_score":0.030405521},"labels":[],"label_agreement":null}]}