{"meta":{"query_hash":"3239adf3675a","filters":{"venue":"Springer series in supply chain management"},"cohort_total":13,"direct_labels_cover":0,"predictions_cover":13,"exported":13,"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/3239adf3675a","api":"https://metacan.xera.ac/api/v1/cohort?venue=Springer+series+in+supply+chain+management"},"results":[{"id":"W2508062625","doi":"10.1007/978-3-319-29791-0_12","title":"Green Technology Choice","year":2016,"lang":"en","type":"book-chapter","venue":"Springer series in supply chain management","topic":"Environmental Sustainability in Business","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"","keywords":"Simple (philosophy); Economics; Business","score_opus":0.007410724778262247,"score_gpt":0.19616331036690304,"score_spread":0.1887525855886408,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2508062625","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0029085486,0.0026816546,0.003437238,0.005268999,0.00045850498,0.000011129197,0.00011098932,0.00004728662,0.98507565],"genre_scores_gemma":[0.11003292,0.0043133115,0.0017133179,0.0014552949,0.00038367757,0.00003658262,0.00017343053,0.00013195371,0.88175946],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9995753,0.00008448003,0.000009120962,0.00007609271,0.00019672677,0.000058260677],"domain_scores_gemma":[0.9996911,0.00010189998,0.000019562836,0.00007951767,0.000053972704,0.000053936117],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005350061,0.0003907588,0.00029405302,0.0009754936,0.0009895797,0.00314919,0.0003746122,0.0013701309,0.08155643],"category_scores_gemma":[0.0013755967,0.00015658111,0.0002883776,0.001227985,0.0017299216,0.0032344565,0.0015634975,0.0017219515,0.013678389],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000015299785,0.00002541376,0.00015042766,0.00003474484,0.0000041749577,0.000027691573,0.00022309905,0.00028785274,0.00021588431,0.878131,0.058224067,0.06266027],"study_design_scores_gemma":[0.000003175363,0.000009046379,0.0003995641,0.00007612851,0.0000029874668,0.00004682209,0.00022711525,0.00030434405,0.00026085085,0.37821478,0.6204488,0.0000063711173],"about_ca_topic_score_codex":0.0013676084,"about_ca_topic_score_gemma":0.0029546125,"teacher_disagreement_score":0.08155643,"about_ca_system_score_codex":0.0018823722,"about_ca_system_score_gemma":0.0010598333,"threshold_uncertainty_score":0.27283347},"labels":[],"label_agreement":null},{"id":"W2982014188","doi":"10.1007/978-3-030-31733-1_8","title":"Price-Matching Strategy: Implications of Consumer Behavior and Channel Structure","year":2019,"lang":"en","type":"book-chapter","venue":"Springer series in supply chain management","topic":"Supply Chain and Inventory Management","field":"Business, Management and Accounting","cited_by":6,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University; Queen's University","funders":"","keywords":"Product (mathematics); Business; Price discrimination; Context (archaeology); Competition (biology); Matching (statistics); Channel (broadcasting); Reservation price; Set (abstract data type); Microeconomics; Advertising; Industrial organization; Marketing; Economics; Computer science; Telecommunications","score_opus":0.016485399559957918,"score_gpt":0.2222913034030268,"score_spread":0.20580590384306888,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W2982014188","genre_codex":"empirical","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":"empirical","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.6316452,0.0016738238,0.044757564,0.0060553583,0.00010408169,0.0001711214,0.0005081932,0.00017270926,0.31491196],"genre_scores_gemma":[0.9749851,0.0005423362,0.0026901988,0.00020128078,0.000045881512,0.000020434962,0.0000874301,0.00003212407,0.02139525],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9998053,0.000055739365,0.0000064388933,0.000042509586,0.000048394006,0.000041687454],"domain_scores_gemma":[0.99847716,0.0010993931,0.00010824151,0.00008433629,0.00013193351,0.000099024386],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00077639805,0.00026723684,0.00040191298,0.00041617997,0.0004109314,0.0028600553,0.0006906876,0.0012686375,0.026479417],"category_scores_gemma":[0.0048691845,0.0002558288,0.00038437342,0.0008557392,0.0006623255,0.0030037258,0.0004365052,0.0008226889,0.0011807515],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00097406487,0.00083198596,0.02634222,0.00021199895,0.00014138629,0.00053148426,0.0012704274,0.015085894,0.0049775713,0.7626936,0.014124694,0.17281467],"study_design_scores_gemma":[0.0001935328,0.00029224713,0.046936385,0.000063252046,0.00015511132,0.00035615143,0.002482154,0.11274535,0.0023091612,0.8229139,0.011486419,0.00006632002],"about_ca_topic_score_codex":0.003006113,"about_ca_topic_score_gemma":0.003259294,"teacher_disagreement_score":0.026479417,"about_ca_system_score_codex":0.0012297836,"about_ca_system_score_gemma":0.00065919675,"threshold_uncertainty_score":0.088582516},"labels":[],"label_agreement":null},{"id":"W4205390994","doi":"10.1007/978-3-030-85855-1_1","title":"Introduction","year":2022,"lang":"en","type":"book-chapter","venue":"Springer series in supply chain management","topic":"Forecasting Techniques and Applications","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Gadget; Computer science; Scope (computer science); Demand forecasting; Operations research; On demand; Data science; Engineering; Multimedia; Algorithm","score_opus":0.04454961424653824,"score_gpt":0.3019480459911112,"score_spread":0.25739843174457294,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4205390994","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.00041506474,0.003731093,0.0075621754,0.0030289632,0.007346878,0.00017934763,0.003935603,0.0015255369,0.9722754],"genre_scores_gemma":[0.0011321022,0.0021851808,0.0023601598,0.0011288857,0.0009448799,0.000100924524,0.0028657734,0.0003865226,0.98889565],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.99927706,0.00006762335,0.00002711904,0.00014392387,0.00041296723,0.00007130254],"domain_scores_gemma":[0.99909484,0.00013097218,0.00003220754,0.00013469183,0.00044383653,0.00016340139],"candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00069662154,0.0010812315,0.00065471756,0.0020597177,0.0011573937,0.0042347936,0.0016343537,0.0016974581,0.63175595],"category_scores_gemma":[0.0025038535,0.00034767078,0.0005946105,0.0019034069,0.000456347,0.0028842608,0.0022886372,0.0017119511,0.54993296],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000024820392,0.000035575886,0.00008737344,0.00017124339,0.0000025748875,0.000045191486,0.0000772403,0.00013804995,0.0004255329,0.019694602,0.77531683,0.20398103],"study_design_scores_gemma":[0.0000016983117,0.0000058760775,0.0000589077,0.0000534526,9.591829e-7,0.000029363668,0.000022107142,0.000028826029,0.00008059787,0.002838191,0.9968773,0.0000025723348],"about_ca_topic_score_codex":0.0020893568,"about_ca_topic_score_gemma":0.0031445455,"teacher_disagreement_score":0.36824405,"about_ca_system_score_codex":0.0010456821,"about_ca_system_score_gemma":0.0018994794,"threshold_uncertainty_score":0.52525544},"labels":[],"label_agreement":null},{"id":"W4205685700","doi":"10.1007/978-3-030-85855-1_8","title":"Conclusion and Advanced Topics","year":2022,"lang":"en","type":"book-chapter","venue":"Springer series in supply chain management","topic":"Forecasting Techniques and Applications","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Computer science; Censoring (clinical trials); Data science; Artificial intelligence; Analytics; Machine learning; Econometrics; Mathematics","score_opus":0.040760605019574465,"score_gpt":0.3116947197022129,"score_spread":0.27093411468263845,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4205685700","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0015129806,0.0829303,0.009068015,0.04857337,0.10306331,0.00015875229,0.0008727196,0.00041015932,0.75341034],"genre_scores_gemma":[0.006823763,0.047519926,0.004862759,0.011836049,0.018901065,0.000088056535,0.0011320219,0.00022764105,0.9086087],"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","domain_scores_codex":[0.9991198,0.00013938808,0.000033466124,0.00015531974,0.0004336511,0.0001183374],"domain_scores_gemma":[0.9988703,0.000103128754,0.00002556901,0.00010222846,0.0006508192,0.00024788184],"candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0014133037,0.0008051321,0.00056574057,0.0016803369,0.0012350561,0.005452762,0.0014405916,0.002162319,0.17444153],"category_scores_gemma":[0.0025752247,0.0002241777,0.0008957163,0.0021803135,0.00063245295,0.0041855043,0.0018867492,0.0023641998,0.08396866],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.00005975558,0.00007635388,0.00010746265,0.00047236917,0.0000072620724,0.00007448129,0.000100343554,0.0002675601,0.00072102924,0.04673205,0.7514226,0.19995879],"study_design_scores_gemma":[0.000004706004,0.000014421358,0.0001398308,0.0001550374,0.000004448218,0.000043648517,0.00008899552,0.00007896003,0.00018126883,0.012360335,0.9869244,0.0000038664266],"about_ca_topic_score_codex":0.0024546047,"about_ca_topic_score_gemma":0.0035803823,"teacher_disagreement_score":0.8255585,"about_ca_system_score_codex":0.0020654504,"about_ca_system_score_gemma":0.0023784607,"threshold_uncertainty_score":0.58356506},"labels":[],"label_agreement":null},{"id":"W4206741575","doi":"10.1007/978-3-030-81423-6_7","title":"Capacity Management in Agricultural Commodity Processing","year":2012,"lang":"en","type":"book-chapter","venue":"Springer series in supply chain management","topic":"Supply Chain and Inventory Management","field":"Business, Management and Accounting","cited_by":1,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Western University","funders":"","keywords":"Profitability index; Investment (military); Portfolio; Yield (engineering); Capacity utilization; Commodity; Economics; Yield management; Revenue; Capacity management; Heuristics; Time horizon; Investment decisions; Microeconomics; Revenue management; Finance; Production (economics); Computer science; Mathematical optimization; Mathematics","score_opus":0.024518920849347692,"score_gpt":0.20821923896656933,"score_spread":0.18370031811722162,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4206741575","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.053005684,0.05681458,0.30967546,0.0076670703,0.0015972379,0.00015766652,0.00038440438,0.0004327545,0.57026523],"genre_scores_gemma":[0.7880194,0.02351913,0.024889233,0.0003124417,0.00086349493,0.00014662225,0.0002172287,0.0002080227,0.1618243],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99957174,0.00012113205,0.000017080165,0.00006466373,0.00013981665,0.00008568758],"domain_scores_gemma":[0.99949,0.0002922881,0.00003461336,0.000046450547,0.00008963488,0.00004693449],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008032316,0.00082932884,0.00043933233,0.00086325366,0.00064648886,0.0027454947,0.0013753913,0.0010345619,0.017899683],"category_scores_gemma":[0.0016422434,0.00036031482,0.00043903865,0.0018937528,0.0014850957,0.0029320635,0.0013064276,0.0010232219,0.0012559574],"study_design_candidate":"not_applicable","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":[0.00005667705,0.00008062226,0.00033215023,0.00027333293,0.000030554656,0.00016087014,0.00026661952,0.24804573,0.0023666923,0.5956291,0.01877877,0.1339789],"study_design_scores_gemma":[0.000010427364,0.0000389464,0.0005924362,0.0002388889,0.000016384938,0.00007549877,0.00044947685,0.16497988,0.0021451646,0.74101096,0.0903985,0.00004343733],"about_ca_topic_score_codex":0.008258981,"about_ca_topic_score_gemma":0.0076527367,"teacher_disagreement_score":0.017899683,"about_ca_system_score_codex":0.0033717297,"about_ca_system_score_gemma":0.001823967,"threshold_uncertainty_score":0.059880435},"labels":[],"label_agreement":null},{"id":"W4235755322","doi":"10.1007/978-3-030-01863-4","title":"Sharing Economy","year":2019,"lang":"en","type":"book","venue":"Springer series in supply chain management","topic":"Sharing Economy and Platforms","field":"Business, Management and Accounting","cited_by":51,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Sharing economy; Crowdsourcing; Consumption (sociology); Context (archaeology); Perspective (graphical); Business; Production (economics); Economy; Knowledge management; Industrial organization; Economic system; Economics; Computer science; Microeconomics; Geography; Sociology; World Wide Web; Social science","score_opus":0.01234234394046273,"score_gpt":0.19290606479980446,"score_spread":0.18056372085934172,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4235755322","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.002718948,0.0013088911,0.007983282,0.0015028308,0.00030729707,0.00001818231,0.00008698194,0.000093862895,0.98597974],"genre_scores_gemma":[0.15787585,0.00466656,0.0035636097,0.000760219,0.0005542739,0.000104133855,0.0003109014,0.00016607884,0.8319984],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.999676,0.00005588976,0.000010569474,0.000060392293,0.00014158507,0.0000555608],"domain_scores_gemma":[0.999742,0.000056225126,0.000020459494,0.00009225164,0.000051922685,0.00003708458],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00027814973,0.0005851056,0.00033448546,0.0008958294,0.0012983313,0.0049611055,0.00056268147,0.0012762964,0.08148117],"category_scores_gemma":[0.0010987635,0.00020680565,0.00030580515,0.0012813287,0.0016223027,0.007112938,0.0031368153,0.0014449024,0.014623274],"study_design_candidate":"not_applicable","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":[0.000007638723,0.000012289157,0.000036651258,0.000028015735,0.0000025524712,0.000026276088,0.00013771217,0.0003541742,0.00015528084,0.9265951,0.031136151,0.04150816],"study_design_scores_gemma":[0.000003093428,0.00001226299,0.00015178621,0.00006671842,0.0000038612134,0.00012631637,0.00027012563,0.001000068,0.0002675957,0.54445696,0.4536343,0.000006950662],"about_ca_topic_score_codex":0.00085430325,"about_ca_topic_score_gemma":0.0009869321,"teacher_disagreement_score":0.08148117,"about_ca_system_score_codex":0.0012735934,"about_ca_system_score_gemma":0.0011035906,"threshold_uncertainty_score":0.2725817},"labels":[],"label_agreement":null},{"id":"W4285379626","doi":"10.1007/978-3-030-81945-3_4","title":"Impact of Blockchain-Driven Accountability in Multi-Sourcing Supply Chains","year":2021,"lang":"en","type":"book-chapter","venue":"Springer series in supply chain management","topic":"Supply Chain and Inventory Management","field":"Business, Management and Accounting","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Accountability; Supply chain; Business; Quality (philosophy); Payment; Industrial organization; Marketing; Finance","score_opus":0.027687210224089823,"score_gpt":0.255779153346721,"score_spread":0.2280919431226312,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4285379626","genre_codex":"methods","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.29468244,0.0094594145,0.34380174,0.028658314,0.0023756626,0.00041020924,0.0012732436,0.0020342534,0.31730473],"genre_scores_gemma":[0.9775325,0.0012513858,0.008990546,0.0002628962,0.00020085034,0.00004515908,0.0001987278,0.000093367744,0.011424626],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9932991,0.0036325068,0.000169566,0.00054312096,0.0017102759,0.00064529106],"domain_scores_gemma":[0.9663023,0.023822375,0.0013292326,0.0039102016,0.0035523528,0.0010836637],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008849367,0.00059995544,0.00065503735,0.00074488315,0.0012491869,0.005515571,0.0016149054,0.0023299793,0.023739425],"category_scores_gemma":[0.03007111,0.00036615,0.0005743251,0.0016025085,0.0021870243,0.011513087,0.0038592955,0.0032353573,0.0023587113],"study_design_candidate":"not_applicable","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":[0.0011850587,0.0004042956,0.0029072415,0.00040818608,0.000087410794,0.00036074754,0.00048843224,0.2060971,0.0030323055,0.60409737,0.015675452,0.16525652],"study_design_scores_gemma":[0.00015578601,0.00031061296,0.0011887702,0.00021663032,0.0000513426,0.00012170056,0.0004419863,0.41703308,0.003360432,0.55584526,0.021221668,0.000052684558],"about_ca_topic_score_codex":0.005062109,"about_ca_topic_score_gemma":0.0037558577,"teacher_disagreement_score":0.023739425,"about_ca_system_score_codex":0.0032145446,"about_ca_system_score_gemma":0.005200657,"threshold_uncertainty_score":0.079416275},"labels":[],"label_agreement":null},{"id":"W4394676702","doi":"10.1007/978-3-031-45565-0_3","title":"Carbon Footprinting in Supply Chains: Measurement, Reporting, and Disclosure","year":2024,"lang":"en","type":"book-chapter","venue":"Springer series in supply chain management","topic":"Environmental Impact and Sustainability","field":"Environmental Science","cited_by":7,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Footprinting; Supply chain; Scope (computer science); Greenhouse gas; Automatic summarization; Environmental economics; Carbon footprint; Carbon fibers; Business; Computer science; Economics; Chemistry; Marketing","score_opus":0.013988999713109008,"score_gpt":0.22207597095516762,"score_spread":0.2080869712420586,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4394676702","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.023219991,0.13585186,0.071797855,0.117986046,0.016111705,0.00025926175,0.003230868,0.00061026687,0.63093215],"genre_scores_gemma":[0.4413705,0.19158804,0.04646537,0.008809978,0.012813524,0.0004522293,0.0034511099,0.0004948805,0.29455435],"study_design_codex":"design_other","study_design_gemma":"not_applicable","domain_scores_codex":[0.9912776,0.0020144114,0.00045702895,0.0004346015,0.005566059,0.00025029678],"domain_scores_gemma":[0.975133,0.014667663,0.0022254302,0.0019476257,0.0055730045,0.00045324583],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0078093573,0.00041006636,0.00031977225,0.001739616,0.00080085895,0.0053631663,0.0007270167,0.0020429252,0.010384845],"category_scores_gemma":[0.03173546,0.00022046275,0.000236483,0.006689831,0.0015969161,0.005679101,0.0014107676,0.0019303159,0.0022786919],"study_design_candidate":"not_applicable","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":[0.000042061256,0.000036643156,0.0027679973,0.00042663672,0.000019131236,0.000074885465,0.0006712846,0.0017061596,0.0009924861,0.24430001,0.20586641,0.54309624],"study_design_scores_gemma":[0.00000662286,0.000056948433,0.0034285577,0.0012930237,0.000016103384,0.00027593737,0.00088701834,0.0033672883,0.00351844,0.1826353,0.80446094,0.000053833584],"about_ca_topic_score_codex":0.0021038975,"about_ca_topic_score_gemma":0.0024399073,"teacher_disagreement_score":0.010384845,"about_ca_system_score_codex":0.0018813405,"about_ca_system_score_gemma":0.0032851277,"threshold_uncertainty_score":0.041300297},"labels":[],"label_agreement":null},{"id":"W4394676825","doi":"10.1007/978-3-031-45565-0_12","title":"Green Technology Choice for Deep Decarbonization","year":2024,"lang":"en","type":"book-chapter","venue":"Springer series in supply chain management","topic":"Environmental Impact and Sustainability","field":"Environmental Science","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Queen's University","funders":"","keywords":"Materials science; Process engineering; Environmental science; Engineering","score_opus":0.005968135814540829,"score_gpt":0.2189129426749159,"score_spread":0.21294480686037506,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4394676825","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.011995384,0.025291443,0.058689453,0.01611459,0.0022801107,0.000042201846,0.00014349332,0.00019920897,0.88524413],"genre_scores_gemma":[0.34077758,0.02912348,0.022466883,0.0036468897,0.0012467753,0.00010606284,0.00014650177,0.00040889054,0.602077],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.99971336,0.00005324603,0.000007319203,0.000053417738,0.00013517246,0.000037519792],"domain_scores_gemma":[0.9997993,0.00009276219,0.000015362186,0.000041724117,0.000028931152,0.0000218788],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005079403,0.0006191195,0.0004419275,0.00048589677,0.0004918548,0.0022549853,0.0005757147,0.0014680176,0.0255245],"category_scores_gemma":[0.00077273115,0.00023825282,0.00038803302,0.0008164389,0.002132493,0.004609099,0.0017633615,0.0027993186,0.0030027996],"study_design_candidate":"not_applicable","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":[0.000017035825,0.000027103179,0.000043763575,0.000096604395,0.00000840517,0.00003053174,0.000069567206,0.002557767,0.0013492252,0.92592037,0.014990577,0.054888956],"study_design_scores_gemma":[0.0000030078058,0.000013276227,0.00007468245,0.00007955776,0.000003739564,0.000022495406,0.000058501257,0.0018771539,0.0007870076,0.86415166,0.13292165,0.00000722692],"about_ca_topic_score_codex":0.0005257031,"about_ca_topic_score_gemma":0.0011998672,"teacher_disagreement_score":0.0255245,"about_ca_system_score_codex":0.0018766936,"about_ca_system_score_gemma":0.0009817315,"threshold_uncertainty_score":0.085387945},"labels":[],"label_agreement":null},{"id":"W4400726035","doi":"10.1007/978-3-031-60867-4_11","title":"Business Model Innovation for Ambulance Systems in Low- and Middle-Income Countries","year":2024,"lang":"en","type":"book-chapter","venue":"Springer series in supply chain management","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Business; Low and middle income countries; Middle income; Economic growth; Economics; Demographic economics; Developing country","score_opus":0.012928213389732093,"score_gpt":0.21409896352923125,"score_spread":0.20117075013949914,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4400726035","genre_codex":"other","genre_gemma":"empirical","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"empirical","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.22187297,0.040823888,0.039097305,0.016617069,0.0009215296,0.00020528543,0.0004149839,0.00033743936,0.6797096],"genre_scores_gemma":[0.81178236,0.024980456,0.016956164,0.00078406144,0.0001751242,0.000113973954,0.0005752213,0.000094337185,0.14453827],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"qualitative","domain_scores_codex":[0.9990565,0.00032832078,0.000033865766,0.00010482209,0.00021719642,0.00025927144],"domain_scores_gemma":[0.9987716,0.00062644464,0.00009555571,0.00010511299,0.000229301,0.00017184467],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015473048,0.00036255445,0.00030506146,0.00092527113,0.001188858,0.0059644347,0.00077172,0.0012011697,0.0113194045],"category_scores_gemma":[0.0024554082,0.00017354198,0.0005468602,0.0026811347,0.0012808302,0.003019518,0.0012794483,0.0014005277,0.001292415],"study_design_candidate":"qualitative","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":[0.00008098117,0.00022638866,0.0067552147,0.00032377086,0.000035088615,0.00031863182,0.003242724,0.016995816,0.0009950832,0.51888686,0.053426787,0.39871272],"study_design_scores_gemma":[0.000025856643,0.0002986106,0.0158572,0.00082079554,0.00003626742,0.00031177336,0.0071550244,0.04132783,0.0022303865,0.13495,0.7969256,0.000060727227],"about_ca_topic_score_codex":0.008433026,"about_ca_topic_score_gemma":0.0076926257,"teacher_disagreement_score":0.0113194045,"about_ca_system_score_codex":0.005749486,"about_ca_system_score_gemma":0.004493388,"threshold_uncertainty_score":0.041715562},"labels":[],"label_agreement":null},{"id":"W4408998909","doi":"10.1007/978-3-031-74994-0_11","title":"Transportation Problems in Humanitarian Supply Chains","year":2025,"lang":"en","type":"book-chapter","venue":"Springer series in supply chain management","topic":"Facility Location and Emergency Management","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"HEC Montréal","funders":"","keywords":"Supply chain; Business; Marketing","score_opus":0.014471017437259339,"score_gpt":0.20432424068045288,"score_spread":0.18985322324319354,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4408998909","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.08069981,0.11686793,0.09774697,0.05804482,0.0036058458,0.0001656645,0.0010360363,0.00011643199,0.6417165],"genre_scores_gemma":[0.5772088,0.1066655,0.010798084,0.0011188143,0.0036211784,0.00018512188,0.00078084937,0.00011192183,0.29950976],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9995963,0.00017740234,0.000017255856,0.000044413613,0.000086549175,0.000078111356],"domain_scores_gemma":[0.998548,0.00097763,0.00012635942,0.0000502475,0.00021263401,0.00008506094],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006053079,0.00077769643,0.0005844468,0.0013479411,0.0017116757,0.004185838,0.0009245049,0.0024208194,0.022714615],"category_scores_gemma":[0.0030316776,0.0005204235,0.0006377912,0.00515264,0.0022755817,0.0045979056,0.0010797246,0.0025504709,0.0010759588],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_system_candidate":false,"about_ca_system_consensus":false,"study_design_scores_codex":[0.000047793277,0.00007617202,0.0008577489,0.0003182603,0.000034977948,0.00046706077,0.00060134905,0.06463348,0.00015400429,0.81527156,0.08265816,0.034879435],"study_design_scores_gemma":[0.000013729424,0.000026339474,0.0006217904,0.00032895504,0.00001664807,0.00021898159,0.0017139988,0.021502994,0.00010711588,0.8749844,0.100442104,0.000023061722],"about_ca_topic_score_codex":0.016454982,"about_ca_topic_score_gemma":0.00942161,"teacher_disagreement_score":0.022714615,"about_ca_system_score_codex":0.0037600317,"about_ca_system_score_gemma":0.0017751439,"threshold_uncertainty_score":0.075987935},"labels":[],"label_agreement":null},{"id":"W4417181549","doi":"10.1007/978-3-032-07054-8_11","title":"Reimagining Supply Chain Planning Using Machine Learning: A Roadmap to Agility and Resilience","year":2025,"lang":"en","type":"book-chapter","venue":"Springer series in supply chain management","topic":"Supply Chain Resilience and Risk Management","field":"Business, Management and Accounting","cited_by":2,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"McGill University","funders":"","keywords":"Supply chain; Resilience (materials science); Supply chain management; Volatility (finance); Supply chain risk management; Scenario planning; Demand forecasting; Sales and operations planning; Decision support system","score_opus":0.014606741285009092,"score_gpt":0.2440926389462294,"score_spread":0.2294858976612203,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W4417181549","genre_codex":"methods","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":null,"domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.007939926,0.011049753,0.96748793,0.003169783,0.0004536321,0.000040557028,0.00023145255,0.0017358063,0.007891056],"genre_scores_gemma":[0.19047317,0.016339371,0.78013074,0.00061153434,0.0009531147,0.00010921446,0.0010525548,0.00090602733,0.009424218],"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","domain_scores_codex":[0.9993393,0.00020968802,0.000043828597,0.00013464311,0.00021301695,0.000059557846],"domain_scores_gemma":[0.9962484,0.0023691026,0.00022737918,0.0005274198,0.0004979427,0.0001296847],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0015999974,0.0014167839,0.0013890928,0.0014295984,0.00039489171,0.0027836862,0.0019204124,0.0012258306,0.0056193015],"category_scores_gemma":[0.0050877645,0.0007235328,0.001101416,0.00280189,0.0009809822,0.005021295,0.0019485459,0.0032348204,0.0013344733],"study_design_candidate":"theoretical_or_conceptual","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":[0.00004338407,0.00006273599,0.0005921216,0.00027015642,0.00008250519,0.00004492185,0.00006829061,0.48563126,0.0010716756,0.022384351,0.009263191,0.48048547],"study_design_scores_gemma":[0.000008646618,0.00002578429,0.00021563734,0.00009546509,0.00002206463,0.00002829569,0.000046476966,0.8790046,0.0008148759,0.10587017,0.013848907,0.000019196501],"about_ca_topic_score_codex":0.0077482453,"about_ca_topic_score_gemma":0.008236071,"teacher_disagreement_score":0.0077482453,"about_ca_system_score_codex":0.0013253241,"about_ca_system_score_gemma":0.002315344,"threshold_uncertainty_score":0.01879841},"labels":[],"label_agreement":null},{"id":"W7113895435","doi":"10.1007/978-3-032-07054-8_19","title":"AI May Be Ready for Supply Chains But Are Supply Chains Ready for AI?","year":2025,"lang":"en","type":"book-chapter","venue":"Springer series in supply chain management","topic":"Supply Chain Resilience and Risk Management","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":false,"route_ca_aff":true,"route_ca_fund":false,"route_ca_venue":false,"route_about_ca":false,"ca_institutions":"Cisco Systems (Canada)","funders":"","keywords":"Supply chain; Transformative learning; Workforce; Process (computing); Key (lock); Investment (military); Analytics; Supply chain management","score_opus":0.02556547036006148,"score_gpt":0.2671226717707208,"score_spread":0.2415572014106593,"validation_status":"score_only:v0-immature-baseline","prediction":{"id":"W7113895435","genre_codex":"other","genre_gemma":"other","domain_codex":null,"domain_gemma":null,"model_version":"metacan-v3-hybrid-931329e0061c","genre_candidate":"other","genre_consensus":"other","domain_candidate":null,"domain_consensus":null,"prediction_status":"machine_predicted_unvalidated","genre_scores_codex":[0.0032110396,0.020350264,0.01305569,0.17568134,0.010515559,0.000042448508,0.00022073563,0.00043589497,0.77648693],"genre_scores_gemma":[0.13132304,0.036522705,0.016093154,0.03843023,0.0075192326,0.00012651723,0.0004524243,0.00051175244,0.769021],"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","domain_scores_codex":[0.9985372,0.00033563905,0.000058508584,0.00018644579,0.00057249767,0.00030967192],"domain_scores_gemma":[0.99598265,0.0012822355,0.00022865068,0.00052018324,0.0010969121,0.00088927324],"candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002574141,0.00054261665,0.00045214084,0.0010086216,0.0025249645,0.01206259,0.0011458456,0.0029768762,0.066434205],"category_scores_gemma":[0.0071306727,0.00034050966,0.0005616553,0.0029734038,0.005358198,0.029116035,0.0026927614,0.006768453,0.017882608],"study_design_candidate":"not_applicable","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":[0.000033868248,0.000029337962,0.00024267912,0.00014440539,0.000009692853,0.00009532761,0.0009739388,0.00035827773,0.00023810288,0.7718667,0.13721111,0.08879651],"study_design_scores_gemma":[0.0000029938572,0.000013141064,0.00017291906,0.00015842602,0.0000027674553,0.000056678375,0.00085927,0.00023802732,0.00013531384,0.25151753,0.7468302,0.000012624338],"about_ca_topic_score_codex":0.00499307,"about_ca_topic_score_gemma":0.0055298125,"teacher_disagreement_score":0.066434205,"about_ca_system_score_codex":0.0029836558,"about_ca_system_score_gemma":0.0034630846,"threshold_uncertainty_score":0.22224456},"labels":[],"label_agreement":null}]}